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https://api.github.com/repos/huggingface/datasets/issues/6458 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6458/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6458/comments | https://api.github.com/repos/huggingface/datasets/issues/6458/events | https://github.com/huggingface/datasets/pull/6458 | 2,016,577,761 | PR_kwDODunzps5gqy4M | 6,458 | Lazy data files resolution | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-11-29T13:18:44Z | 2024-02-08T14:41:35Z | 2024-02-08T14:41:35Z | MEMBER | null | null | null | Related to discussion at https://github.com/huggingface/datasets/pull/6255
this makes this code run in 2sec instead of >10sec
```python
from datasets import load_dataset
ds = load_dataset("glue", "sst2", streaming=True, trust_remote_code=False)
```
For some datasets with many configs and files it can be up to 100x faster.
This is particularly important now that some datasets will be loaded from the Parquet export instead of the scripts.
The data files are only resolved in the builder `__init__`. To do so I added DataFilesPatternsList and DataFilesPatternsDict that have `.resolve()` to return resolved DataFilesList and DataFilesDict | {
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https://api.github.com/repos/huggingface/datasets/issues/7485 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7485/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7485/comments | https://api.github.com/repos/huggingface/datasets/issues/7485/events | https://github.com/huggingface/datasets/pull/7485 | 2,953,696,519 | PR_kwDODunzps6QbjFJ | 7,485 | set dev version | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7485). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2025-03-27T16:39:34Z | 2025-03-27T16:41:59Z | 2025-03-27T16:39:42Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4760 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4760/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4760/comments | https://api.github.com/repos/huggingface/datasets/issues/4760/events | https://github.com/huggingface/datasets/issues/4760 | 1,320,878,223 | I_kwDODunzps5OuwCP | 4,760 | Issue with offline mode | {
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"Hi @SaulLu, thanks for reporting.\r\n\r\nI think offline mode is not supported for datasets containing only data files (without any loading script). I'm having a look into this...",
"Thanks for your feedback! \r\n\r\nTo give you a little more info, if you don't set the offline mode flag, the script will load the... | 2022-07-28T12:45:14Z | 2024-03-25T16:24:45Z | 2024-01-23T10:58:22Z | CONTRIBUTOR | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ## Describe the bug
I can't retrieve a cached dataset with offline mode enabled
## Steps to reproduce the bug
To reproduce my issue, first, you'll need to run a script that will cache the dataset
```python
import os
os.environ["HF_DATASETS_OFFLINE"] = "0"
import datasets
datasets.logging.set_verbosity_info()
ds_name = "SaulLu/toy_struc_dataset"
ds = datasets.load_dataset(ds_name)
print(ds)
```
then, you can try to reload it in offline mode:
```python
import os
os.environ["HF_DATASETS_OFFLINE"] = "1"
import datasets
datasets.logging.set_verbosity_info()
ds_name = "SaulLu/toy_struc_dataset"
ds = datasets.load_dataset(ds_name)
print(ds)
```
## Expected results
I would have expected the 2nd snippet not to return any errors
## Actual results
The 2nd snippet returns:
```
Traceback (most recent call last):
File "/home/lucile_huggingface_co/sandbox/evaluate/test_cache_datasets.py", line 8, in <module>
ds = datasets.load_dataset(ds_name)
File "/home/lucile_huggingface_co/anaconda3/envs/evaluate-dev/lib/python3.8/site-packages/datasets/load.py", line 1723, in load_dataset
builder_instance = load_dataset_builder(
File "/home/lucile_huggingface_co/anaconda3/envs/evaluate-dev/lib/python3.8/site-packages/datasets/load.py", line 1500, in load_dataset_builder
dataset_module = dataset_module_factory(
File "/home/lucile_huggingface_co/anaconda3/envs/evaluate-dev/lib/python3.8/site-packages/datasets/load.py", line 1241, in dataset_module_factory
raise ConnectionError(f"Couln't reach the Hugging Face Hub for dataset '{path}': {e1}") from None
ConnectionError: Couln't reach the Hugging Face Hub for dataset 'SaulLu/toy_struc_dataset': Offline mode is enabled.
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.4.0
- Platform: Linux-4.19.0-21-cloud-amd64-x86_64-with-glibc2.17
- Python version: 3.8.13
- PyArrow version: 8.0.0
- Pandas version: 1.4.3
Maybe I'm misunderstanding something in the use of the offline mode (see [doc](https://huggingface.co/docs/datasets/v2.4.0/en/loading#offline)), is that the case?
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https://api.github.com/repos/huggingface/datasets/issues/5336 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5336/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5336/comments | https://api.github.com/repos/huggingface/datasets/issues/5336/events | https://github.com/huggingface/datasets/pull/5336 | 1,479,649,900 | PR_kwDODunzps5Egzed | 5,336 | Set `IterableDataset.map` param `batch_size` typing as optional | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5336). All of your documentation changes will be reflected on that endpoint.",
"Hi @mariosasko, @lhoestq I was wondering whether we should include `batched` as a `pytest.mark` param for the functions testing `IterableDataset.ma... | 2022-12-06T17:08:10Z | 2022-12-07T14:14:56Z | 2022-12-07T14:06:27Z | MEMBER | null | null | null | This PR solves #5325
~Indeed we're using the typing for optional values as `Union[type, None]` as it's similar to how Python 3.10 handles optional values as `type | None`, instead of using `Optional[type]`.~
~Do we want to start using `Union[type, None]` for type-hinting optional values or just keep on using `Optional`?~ -> Keeping `Optional` still for consistency with the rest of the code in `datasets`
Also we now allow `batch_size` to be `None` for `IterableDataset.map` and `IterableDataset.filter`e.g. `MappedExamplesIterable` as `map` is internally instantiating those and propagating the `batch_size` param so if it can be `None` for `map` it should also do so for `MappedExamplesIterable`, as well as for `FilteredExamplesIterable` when calling `IterableDataset.filter`.
## TODOs
- [x] Add integration tests
- [x] Handle scenario where `batched=True` and `batch_size=None` or `batch_size<=0` | {
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https://api.github.com/repos/huggingface/datasets/issues/7423 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7423/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7423/comments | https://api.github.com/repos/huggingface/datasets/issues/7423/events | https://github.com/huggingface/datasets/issues/7423 | 2,879,271,409 | I_kwDODunzps6rnjHx | 7,423 | Row indexing a dataset with numpy integers | {
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"Would be cool to be consistent when it comes to indexing with numpy objects, if we do accept numpy arrays we should indeed accept numpy integers. Your idea sounds reasonable, I'd also be in favor of adding a simple test as well"
] | 2025-02-25T18:44:45Z | 2025-03-03T17:55:24Z | null | NONE | null | null | {
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} | ### Feature request
Allow indexing datasets with a scalar numpy integer type.
### Motivation
Indexing a dataset with a scalar numpy.int* object raises a TypeError. This is due to the test in `datasets/formatting/formatting.py:key_to_query_type`
``` python
def key_to_query_type(key: Union[int, slice, range, str, Iterable]) -> str:
if isinstance(key, int):
return "row"
elif isinstance(key, str):
return "column"
elif isinstance(key, (slice, range, Iterable)):
return "batch"
_raise_bad_key_type(key)
```
In the row case, it checks if key is an int, which returns false when key is integer like but not a builtin python integer type. This is counterintuitive because a numpy array of np.int64s can be used for the batch case.
For example:
``` python
import numpy as np
import datasets
dataset = datasets.Dataset.from_dict({"a": [1, 2, 3, 4], "b": [5, 6, 7, 8]})
# Regular indexing
dataset[0]
dataset[:2]
# Indexing with numpy data types (expect same results)
idx = np.asarray([0, 1])
dataset[idx] # Succeeds when using an array of np.int64 values
dataset[idx[0]] # Fails with TypeError when using scalar np.int64
```
For the user, this can be solved by wrapping `idx[0]` in `int` but the test could also be changed in `key_to_query_type` to accept a less strict definition of int.
``` diff
+import numbers
+
def key_to_query_type(key: Union[int, slice, range, str, Iterable]) -> str:
+ if isinstance(key, numbers.Integral):
- if isinstance(key, int):
return "row"
elif isinstance(key, str):
return "column"
elif isinstance(key, (slice, range, Iterable)):
return "batch"
_raise_bad_key_type(key)
```
Looking at how others do it, pandas has an `is_integer` definition that it checks which uses `is_integer_object` defined in `pandas/_libs/utils.pxd`:
``` cython
cdef inline bint is_integer_object(object obj) noexcept:
"""
Cython equivalent of
`isinstance(val, (int, np.integer)) and not isinstance(val, (bool, np.timedelta64))`
Parameters
----------
val : object
Returns
-------
is_integer : bool
Notes
-----
This counts np.timedelta64 objects as integers.
"""
return (not PyBool_Check(obj) and isinstance(obj, (int, cnp.integer))
and not is_timedelta64_object(obj))
```
This would be less flexible as it explicitly checks for numpy integer, but worth noting that they had the need to ensure the key is not a bool.
### Your contribution
I can submit a pull request with the above changes after checking that indexing succeeds with the numpy integer type. Or if there is a different integer check that would be preferred I could add that.
If there is a reason not to want this behavior that is fine too.
| null | {
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https://api.github.com/repos/huggingface/datasets/issues/6809 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6809/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6809/comments | https://api.github.com/repos/huggingface/datasets/issues/6809/events | https://github.com/huggingface/datasets/pull/6809 | 2,242,956,297 | PR_kwDODunzps5so0e2 | 6,809 | Make convert_to_parquet CLI command create script branch | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6809). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"@huggingface/datasets once this PR is merged, I would suggest making a release. Do you ... | 2024-04-15T07:47:26Z | 2024-04-17T08:44:26Z | 2024-04-17T08:38:18Z | MEMBER | null | null | null | Make convert_to_parquet CLI command create a "script" branch and keep the script file on it.
This PR proposes the simplest UX approach: whenever `--revision` is not explicitly passed (i.e., when the script is in the main branch), try to create a "script" branch from the "main" branch; if the "script" branch exists already, then do nothing.
Follow-up of:
- #6795
Close #6808.
CC: @severo | {
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https://api.github.com/repos/huggingface/datasets/issues/6853 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6853/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6853/comments | https://api.github.com/repos/huggingface/datasets/issues/6853/events | https://github.com/huggingface/datasets/issues/6853 | 2,272,570,000 | I_kwDODunzps6HdKqQ | 6,853 | Support soft links for load_datasets imagefolder | {
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"completed": 0,
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} | ### Feature request
Load_dataset from a folder of images doesn't seem to support soft links. It would be nice if it did, especially during methods development where image folders are being curated.
### Motivation
Images are coming from a complex variety of sources and we'd like to be able to soft link directly from the originating folders as opposed to copying. Having a copy of the file ensures that there may be issues with image versioning as well as having double the amount of required disk space.
### Your contribution
N/A | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6796 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6796/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6796/comments | https://api.github.com/repos/huggingface/datasets/issues/6796/events | https://github.com/huggingface/datasets/issues/6796 | 2,234,887,618 | I_kwDODunzps6FNa3C | 6,796 | CI is broken due to hf-internal-testing/dataset_with_script | {
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"Finally:\r\n- the initial issue seems it was temporary\r\n- there is a different issue now: https://github.com/huggingface/datasets/actions/runs/8627153993/job/23646584590?pr=6797\r\n```\r\nFAILED tests/test_load.py::ModuleFactoryTest::test_HubDatasetModuleFactoryWithParquetExport - datasets.utils._dataset_viewer.... | 2024-04-10T06:56:02Z | 2024-04-12T09:02:13Z | 2024-04-12T09:02:13Z | MEMBER | null | null | {
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"total": 0
} | CI is broken for test_load_dataset_distributed_with_script. See: https://github.com/huggingface/datasets/actions/runs/8614926216/job/23609378127
```
FAILED tests/test_load.py::test_load_dataset_distributed_with_script[None] - assert False
+ where False = all(<generator object test_load_dataset_distributed_with_script.<locals>.<genexpr> at 0x7f0c741de3b0>)
FAILED tests/test_load.py::test_load_dataset_distributed_with_script[force_redownload] - assert False
+ where False = all(<generator object test_load_dataset_distributed_with_script.<locals>.<genexpr> at 0x7f0be45f6ea0>)
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/4543 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4543/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4543/comments | https://api.github.com/repos/huggingface/datasets/issues/4543/events | https://github.com/huggingface/datasets/pull/4543 | 1,280,379,781 | PR_kwDODunzps46IiEp | 4,543 | [CI] Fix upstream hub test url | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Remaining CI failures are unrelated to this fix, merging"
] | 2022-06-22T15:34:27Z | 2022-06-22T16:37:40Z | 2022-06-22T16:27:37Z | MEMBER | null | null | null | Some tests were still using moon-stagign instead of hub-ci.
I also updated the token to use one dedicated to `datasets` | {
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https://api.github.com/repos/huggingface/datasets/issues/6277 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6277/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6277/comments | https://api.github.com/repos/huggingface/datasets/issues/6277/events | https://github.com/huggingface/datasets/issues/6277 | 1,927,044,546 | I_kwDODunzps5y3F3C | 6,277 | FileNotFoundError: Couldn't find a module script at /content/paws-x/paws-x.py. Module 'paws-x' doesn't exist on the Hugging Face Hub either. | {
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"`evaluate.load(\"paws-x\", \"es\")` throws the error because there is no such metric in the `evaluate` lib.\r\n\r\nSo, this is unrelated to our lib."
] | 2023-10-04T22:01:25Z | 2023-10-08T17:05:46Z | 2023-10-08T17:05:46Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
I'm encountering a "FileNotFoundError" while attempting to use the "paws-x" dataset to retrain the DistilRoBERTa-base model. The error message is as follows:
FileNotFoundError: Couldn't find a module script at /content/paws-x/paws-x.py. Module 'paws-x' doesn't exist on the Hugging Face Hub either.
### Steps to reproduce the bug
https://colab.research.google.com/drive/11xUUFxloClpmqLvDy_Xxfmo3oUzjY5nx#scrollTo=kUn74FigzhHm
### Expected behavior
The the trained model
### Environment info
colab, "paws-x" dataset , DistilRoBERTa-base model | {
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https://api.github.com/repos/huggingface/datasets/issues/5679 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5679/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5679/comments | https://api.github.com/repos/huggingface/datasets/issues/5679/events | https://github.com/huggingface/datasets/issues/5679 | 1,645,184,622 | I_kwDODunzps5iD4Zu | 5,679 | Allow load_dataset to take a working dir for intermediate data | {
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"Hi ! AFAIK a dataset must be present on a local disk to be able to efficiently memory map the datasets Arrow files. What makes you think that it is possible to load from a cloud storage and have good performance ?\r\n\r\nAnyway it's already possible to download_and_prepare a dataset as Arrow files in a cloud stora... | 2023-03-29T07:21:09Z | 2023-04-12T22:30:25Z | null | NONE | null | null | {
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} | ### Feature request
As a user, I can set a working dir for intermediate data creation. The processed files will be moved to the cache dir, like
```
load_dataset(…, working_dir=”/temp/dir”, cache_dir=”/cloud_dir”).
```
### Motivation
This will help the use case for using datasets with cloud storage as cache. It will help boost the performance.
### Your contribution
I can provide a PR to fix this if the proposal seems reasonable. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7033 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7033/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7033/comments | https://api.github.com/repos/huggingface/datasets/issues/7033/events | https://github.com/huggingface/datasets/issues/7033 | 2,397,419,768 | I_kwDODunzps6O5bj4 | 7,033 | `from_generator` does not allow to specify the split name | {
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"Thanks for reporting, @pminervini.\r\n\r\nI agree we should give the option to define the split name.\r\n\r\nIndeed, there is a PR that addresses precisely this issue:\r\n- #7015\r\n\r\nI am reviewing it.",
"Booom! thank you guys :)"
] | 2024-07-09T07:47:58Z | 2024-07-26T12:56:16Z | 2024-07-26T09:31:56Z | CONTRIBUTOR | null | null | {
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} | ### Describe the bug
I'm building train, dev, and test using `from_generator`; however, in all three cases, the logger prints `Generating train split:`
It's not possible to change the split name since it seems to be hardcoded: https://github.com/huggingface/datasets/blob/main/src/datasets/packaged_modules/generator/generator.py
### Steps to reproduce the bug
```
In [1]: from datasets import Dataset
In [2]: def gen():
...: yield {"pokemon": "bulbasaur", "type": "grass"}
...:
In [3]: ds = Dataset.from_generator(gen)
Generating train split: 1 examples [00:00, 133.89 examples/s]
```
### Expected behavior
It should be possible to specify any split name
### Environment info
- `datasets` version: 2.19.2
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.8.5
- `huggingface_hub` version: 0.23.3
- PyArrow version: 15.0.0
- Pandas version: 2.0.3
- `fsspec` version: 2023.10.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5886 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5886/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5886/comments | https://api.github.com/repos/huggingface/datasets/issues/5886/events | https://github.com/huggingface/datasets/issues/5886 | 1,721,070,225 | I_kwDODunzps5mlXKR | 5,886 | Use work-stealing algorithm when parallel computing | {
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"Alternatively we could set the number of shards to be a factor than the number of processes (current they're equal) - this way it will be less likely to end up with a shard that is significantly slower than all the other ones."
] | 2023-05-23T03:08:44Z | 2023-05-24T15:30:09Z | null | NONE | null | null | {
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} | ### Feature request
when i used Dataset.map api to process data concurrently, i found that
it gets slower and slower as it gets closer to completion. Then i read the source code of arrow_dataset.py and found that it shard the dataset and use multiprocessing pool to execute each shard.It may cause the slowest task to drag out the entire program's execution time,especially when processing huge dataset.
### Motivation
using work-stealing algorithm instead of sharding and parallel computing to optimize performance.
### Your contribution
just an idea. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5897 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5897/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5897/comments | https://api.github.com/repos/huggingface/datasets/issues/5897/events | https://github.com/huggingface/datasets/pull/5897 | 1,726,135,494 | PR_kwDODunzps5RXJaY | 5,897 | Fix `FixedSizeListArray` casting | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-05-25T16:26:33Z | 2023-05-26T12:22:04Z | 2023-05-26T11:57:16Z | COLLABORATOR | null | null | null | Fix cast on sliced `FixedSizeListArray`s.
Fix #5866 | {
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https://api.github.com/repos/huggingface/datasets/issues/5978 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5978/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5978/comments | https://api.github.com/repos/huggingface/datasets/issues/5978/events | https://github.com/huggingface/datasets/pull/5978 | 1,770,187,053 | PR_kwDODunzps5Tru2_ | 5,978 | Release: 2.13.1 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-06-22T18:23:11Z | 2023-06-22T18:40:24Z | 2023-06-22T18:30:16Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7321 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7321/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7321/comments | https://api.github.com/repos/huggingface/datasets/issues/7321/events | https://github.com/huggingface/datasets/issues/7321 | 2,731,626,760 | I_kwDODunzps6i0VEI | 7,321 | ImportError: cannot import name 'set_caching_enabled' from 'datasets' | {
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"pip install datasets==2.18.0",
"Hi ! I think you need to update axolotl"
] | 2024-12-11T01:58:46Z | 2024-12-11T13:32:15Z | null | NONE | null | null | {
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} | ### Describe the bug
Traceback (most recent call last):
File "/usr/local/lib/python3.10/runpy.py", line 187, in _run_module_as_main
mod_name, mod_spec, code = _get_module_details(mod_name, _Error)
File "/usr/local/lib/python3.10/runpy.py", line 110, in _get_module_details
__import__(pkg_name)
File "/home/Medusa/axolotl/src/axolotl/cli/__init__.py", line 23, in <module>
from axolotl.train import TrainDatasetMeta
File "/home/Medusa/axolotl/src/axolotl/train.py", line 23, in <module>
from axolotl.utils.trainer import setup_trainer
File "/home/Medusa/axolotl/src/axolotl/utils/trainer.py", line 13, in <module>
from datasets import set_caching_enabled
ImportError: cannot import name 'set_caching_enabled' from 'datasets' (/usr/local/lib/python3.10/site-packages/datasets/__init__.py)
### Steps to reproduce the bug
1、axolotl
2、accelerate launch -m axolotl.cli.train examples/medusa/qwen_lora_stage1.yml
### Expected behavior
enable datasets
### Environment info
python3.10 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6296 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6296/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6296/comments | https://api.github.com/repos/huggingface/datasets/issues/6296/events | https://github.com/huggingface/datasets/pull/6296 | 1,938,453,845 | PR_kwDODunzps5cjUs1 | 6,296 | Move `exceptions.py` to `utils/exceptions.py` | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-10-11T18:28:00Z | 2024-09-03T16:00:04Z | 2024-09-03T16:00:03Z | COLLABORATOR | null | null | null | I didn't notice the path while reviewing the PR yesterday :( | {
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https://api.github.com/repos/huggingface/datasets/issues/7251 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7251/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7251/comments | https://api.github.com/repos/huggingface/datasets/issues/7251/events | https://github.com/huggingface/datasets/pull/7251 | 2,612,097,435 | PR_kwDODunzps5_zPTt | 7,251 | Missing video docs | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7251). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2024-10-24T16:45:12Z | 2024-10-24T16:48:29Z | 2024-10-24T16:48:27Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5989 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5989/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5989/comments | https://api.github.com/repos/huggingface/datasets/issues/5989/events | https://github.com/huggingface/datasets/issues/5989 | 1,774,134,091 | I_kwDODunzps5pvyNL | 5,989 | Set a rule on the config and split names | {
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"in this case we need to decide what to do with the existing datasets with white space characters (there shouldn't be a lot of them I think)",
"I imagine that we should stop supporting them, and help the user fix them?",
"See a report where the datasets server fails: https://huggingface.co/datasets/poloclub/dif... | 2023-06-26T07:34:14Z | 2023-07-19T14:22:54Z | null | COLLABORATOR | null | null | {
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} | > should we actually allow characters like spaces? maybe it's better to add validation for whitespace symbols and directly in datasets and raise
https://github.com/huggingface/datasets-server/issues/853
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https://api.github.com/repos/huggingface/datasets/issues/7236 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7236/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7236/comments | https://api.github.com/repos/huggingface/datasets/issues/7236/events | https://github.com/huggingface/datasets/pull/7236 | 2,597,358,525 | PR_kwDODunzps5_GIvw | 7,236 | [MINOR:TYPO] Update arrow_dataset.py | {
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csv kwargs docstring link was pointing to pandas json docs. | {
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https://api.github.com/repos/huggingface/datasets/issues/6880 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6880/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6880/comments | https://api.github.com/repos/huggingface/datasets/issues/6880/events | https://github.com/huggingface/datasets/issues/6880 | 2,283,278,337 | I_kwDODunzps6IGBAB | 6,880 | Webdataset: KeyError: 'png' on some datasets when streaming | {
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"The error is caused by malformed basenames of the files within the TARs:\r\n- `15_Cohen_1-s2.0-S0929664620300449-gr3_lrg-b.png` becomes `15_Cohen_1-s2` as the grouping `__key__`, and `0-S0929664620300449-gr3_lrg-b.png` as the additional key to be added to the example\r\n- whereas the intended behavior was to use `... | 2024-05-07T13:09:02Z | 2024-05-14T20:34:05Z | null | MEMBER | null | null | {
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} | reported at https://huggingface.co/datasets/tbone5563/tar_images/discussions/1
```python
>>> from datasets import load_dataset
>>> ds = load_dataset("tbone5563/tar_images")
Downloading data: 100%
1.41G/1.41G [00:48<00:00, 17.2MB/s]
Downloading data: 100%
619M/619M [00:11<00:00, 57.4MB/s]
Generating train split:
970/0 [00:02<00:00, 534.94 examples/s]
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
[/usr/local/lib/python3.10/dist-packages/datasets/builder.py](https://localhost:8080/#) in _prepare_split_single(self, gen_kwargs, fpath, file_format, max_shard_size, split_info, check_duplicate_keys, job_id)
1747 _time = time.time()
-> 1748 for key, record in generator:
1749 if max_shard_size is not None and writer._num_bytes > max_shard_size:
7 frames
[/usr/local/lib/python3.10/dist-packages/datasets/packaged_modules/webdataset/webdataset.py](https://localhost:8080/#) in _generate_examples(self, tar_paths, tar_iterators)
108 for field_name in image_field_names + audio_field_names:
--> 109 example[field_name] = {"path": example["__key__"] + "." + field_name, "bytes": example[field_name]}
110 yield f"{tar_idx}_{example_idx}", example
KeyError: 'png'
The above exception was the direct cause of the following exception:
DatasetGenerationError Traceback (most recent call last)
[<ipython-input-2-8e0fbb7badc9>](https://localhost:8080/#) in <cell line: 3>()
1 from datasets import load_dataset
2
----> 3 ds = load_dataset("tbone5563/tar_images")
[/usr/local/lib/python3.10/dist-packages/datasets/load.py](https://localhost:8080/#) in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, ignore_verifications, keep_in_memory, save_infos, revision, token, use_auth_token, task, streaming, num_proc, storage_options, trust_remote_code, **config_kwargs)
2607
2608 # Download and prepare data
-> 2609 builder_instance.download_and_prepare(
2610 download_config=download_config,
2611 download_mode=download_mode,
[/usr/local/lib/python3.10/dist-packages/datasets/builder.py](https://localhost:8080/#) in download_and_prepare(self, output_dir, download_config, download_mode, verification_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, file_format, max_shard_size, num_proc, storage_options, **download_and_prepare_kwargs)
1025 if num_proc is not None:
1026 prepare_split_kwargs["num_proc"] = num_proc
-> 1027 self._download_and_prepare(
1028 dl_manager=dl_manager,
1029 verification_mode=verification_mode,
[/usr/local/lib/python3.10/dist-packages/datasets/builder.py](https://localhost:8080/#) in _download_and_prepare(self, dl_manager, verification_mode, **prepare_splits_kwargs)
1787
1788 def _download_and_prepare(self, dl_manager, verification_mode, **prepare_splits_kwargs):
-> 1789 super()._download_and_prepare(
1790 dl_manager,
1791 verification_mode,
[/usr/local/lib/python3.10/dist-packages/datasets/builder.py](https://localhost:8080/#) in _download_and_prepare(self, dl_manager, verification_mode, **prepare_split_kwargs)
1120 try:
1121 # Prepare split will record examples associated to the split
-> 1122 self._prepare_split(split_generator, **prepare_split_kwargs)
1123 except OSError as e:
1124 raise OSError(
[/usr/local/lib/python3.10/dist-packages/datasets/builder.py](https://localhost:8080/#) in _prepare_split(self, split_generator, check_duplicate_keys, file_format, num_proc, max_shard_size)
1625 job_id = 0
1626 with pbar:
-> 1627 for job_id, done, content in self._prepare_split_single(
1628 gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
1629 ):
[/usr/local/lib/python3.10/dist-packages/datasets/builder.py](https://localhost:8080/#) in _prepare_split_single(self, gen_kwargs, fpath, file_format, max_shard_size, split_info, check_duplicate_keys, job_id)
1782 if isinstance(e, SchemaInferenceError) and e.__context__ is not None:
1783 e = e.__context__
-> 1784 raise DatasetGenerationError("An error occurred while generating the dataset") from e
1785
1786 yield job_id, True, (total_num_examples, total_num_bytes, writer._features, num_shards, shard_lengths)
DatasetGenerationError: An error occurred while generating the dataset
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https://api.github.com/repos/huggingface/datasets/issues/6244 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6244/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6244/comments | https://api.github.com/repos/huggingface/datasets/issues/6244/events | https://github.com/huggingface/datasets/pull/6244 | 1,898,861,422 | PR_kwDODunzps5adtD3 | 6,244 | Add support for `fsspec>=2023.9.0` | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-09-15T17:58:25Z | 2023-09-26T15:41:38Z | 2023-09-26T15:32:51Z | COLLABORATOR | null | null | null | Fix #6214 | {
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https://api.github.com/repos/huggingface/datasets/issues/5264 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5264/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5264/comments | https://api.github.com/repos/huggingface/datasets/issues/5264/events | https://github.com/huggingface/datasets/issues/5264 | 1,455,252,906 | I_kwDODunzps5WvWWq | 5,264 | `datasets` can't read a Parquet file in Python 3.9.13 | {
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] | closed | false | null | [] | null | [
"Could you share the full stack trace please ?\r\n\r\n\r\nCan you also try running this code ? It can be useful to determine if the issue comes from `datasets` or `fsspec` (streaming) or `pyarrow` (parquet reading):\r\n```python\r\nds = load_dataset(\"parquet\", data_files=a_parquet_file_url, use_auth_token=True)\r... | 2022-11-18T14:44:01Z | 2023-05-07T09:52:59Z | 2022-11-22T11:18:08Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
I have an error when trying to load this [dataset](https://huggingface.co/datasets/bigcode/the-stack-dedup-pjj) (it's private but I can add you to the bigcode org). `datasets` can't read one of the parquet files in the Java subset
```python
from datasets import load_dataset
ds = load_dataset("bigcode/the-stack-dedup-pjj", data_dir="data/java", split="train", revision="v1.1.a1", use_auth_token=True)
````
```
File "pyarrow/error.pxi", line 100, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.
```
It seems to be an issue with new Python versions, Because it works in these two environements:
```
- `datasets` version: 2.6.1
- Platform: Linux-5.4.0-131-generic-x86_64-with-glibc2.31
- Python version: 3.9.7
- PyArrow version: 9.0.0
- Pandas version: 1.3.4
```
```
- `datasets` version: 2.6.1
- Platform: Linux-4.19.0-22-cloud-amd64-x86_64-with-debian-10.13
- Python version: 3.7.12
- PyArrow version: 9.0.0
- Pandas version: 1.3.4
```
But not in this:
```
- `datasets` version: 2.6.1
- Platform: Linux-4.19.0-22-cloud-amd64-x86_64-with-glibc2.28
- Python version: 3.9.13
- PyArrow version: 9.0.0
- Pandas version: 1.3.4
```
### Steps to reproduce the bug
Load the dataset in python 3.9.13
### Expected behavior
Load the dataset without the pyarrow error.
### Environment info
```
- `datasets` version: 2.6.1
- Platform: Linux-4.19.0-22-cloud-amd64-x86_64-with-glibc2.28
- Python version: 3.9.13
- PyArrow version: 9.0.0
- Pandas version: 1.3.4
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/7355 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7355/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7355/comments | https://api.github.com/repos/huggingface/datasets/issues/7355/events | https://github.com/huggingface/datasets/issues/7355 | 2,768,958,211 | I_kwDODunzps6lCvMD | 7,355 | Not available datasets[audio] on python 3.13 | {
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"It looks like an issue with `numba` which can't be installed on 3.13 ? `numba` is a dependency of `librosa`, used to decode audio files"
] | 2025-01-04T18:37:08Z | 2025-01-10T10:46:00Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
This is the error I got, it seems numba package does not support python 3.13
PS C:\Users\sergi\Documents> pip install datasets[audio]
Defaulting to user installation because normal site-packages is not writeable
Collecting datasets[audio]
Using cached datasets-3.2.0-py3-none-any.whl.metadata (20 kB)
... (OTHER PACKAGES)
Collecting numba>=0.51.0 (from librosa->datasets[audio])
Downloading numba-0.60.0.tar.gz (2.7 MB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 2.7/2.7 MB 44.1 MB/s eta 0:00:00
Installing build dependencies ... done
Getting requirements to build wheel ... error
error: subprocess-exited-with-error
× Getting requirements to build wheel did not run successfully.
│ exit code: 1
╰─> [24 lines of output]
Traceback (most recent call last):
File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.13_3.13.496.0_x64__qbz5n2kfra8p0\Lib\site-packages\pip\_vendor\pyproject_hooks\_in_process\_in_process.py", line 353, in <module>
main()
~~~~^^
File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.13_3.13.496.0_x64__qbz5n2kfra8p0\Lib\site-packages\pip\_vendor\pyproject_hooks\_in_process\_in_process.py", line 335, in main
json_out['return_val'] = hook(**hook_input['kwargs'])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.13_3.13.496.0_x64__qbz5n2kfra8p0\Lib\site-packages\pip\_vendor\pyproject_hooks\_in_process\_in_process.py", line 118, in get_requires_for_build_wheel
return hook(config_settings)
File "C:\Users\sergi\AppData\Local\Temp\pip-build-env-yauns_qh\overlay\Lib\site-packages\setuptools\build_meta.py", line 334, in get_requires_for_build_wheel
return self._get_build_requires(config_settings, requirements=[])
~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\sergi\AppData\Local\Temp\pip-build-env-yauns_qh\overlay\Lib\site-packages\setuptools\build_meta.py", line 304, in _get_build_requires
self.run_setup()
~~~~~~~~~~~~~~^^
RuntimeError: Cannot install on Python version 3.13.1; only versions >=3.9,<3.13 are supported.
[end of output]
note: This error originates from a subprocess, and is likely not a problem with pip.
error: subprocess-exited-with-error
× Getting requirements to build wheel did not run successfully.
│ exit code: 1
╰─> See above for output.
### Steps to reproduce the bug
1. install python >=3.13
2. !pip install datasets[audio]
### Expected behavior
I needed datasets[audio] in the python 3.13
### Environment info
python 3.13.1 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7362 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7362/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7362/comments | https://api.github.com/repos/huggingface/datasets/issues/7362/events | https://github.com/huggingface/datasets/issues/7362 | 2,773,731,829 | I_kwDODunzps6lU8n1 | 7,362 | HuggingFace CLI dataset download raises error | {
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"I got the same error and was able to resolve it by upgrading from 2.15.0 to 3.2.0.",
"> I got the same error and was able to resolve it by upgrading from 2.15.0 to 3.2.0.\r\n\r\nWhat is needed is upgrading `huggingface-hub==0.27.1`. `datasets` does not appear to have anything to do with the error. The upgrade is... | 2025-01-07T21:03:30Z | 2025-01-08T15:00:37Z | 2025-01-08T14:35:52Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
Trying to download Hugging Face datasets using Hugging Face CLI raises error. This error only started after December 27th, 2024. For example:
```
huggingface-cli download --repo-type dataset gboleda/wikicorpus
Traceback (most recent call last):
File "/home/ubuntu/test_venv/bin/huggingface-cli", line 8, in <module>
sys.exit(main())
File "/home/ubuntu/test_venv/lib/python3.10/site-packages/huggingface_hub/commands/huggingface_cli.py", line 51, in main
service.run()
File "/home/ubuntu/test_venv/lib/python3.10/site-packages/huggingface_hub/commands/download.py", line 146, in run
print(self._download()) # Print path to downloaded files
File "/home/ubuntu/test_venv/lib/python3.10/site-packages/huggingface_hub/commands/download.py", line 180, in _download
return snapshot_download(
File "/home/ubuntu/test_venv/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
return fn(*args, **kwargs)
File "/home/ubuntu/test_venv/lib/python3.10/site-packages/huggingface_hub/_snapshot_download.py", line 164, in snapshot_download
repo_info = api.repo_info(repo_id=repo_id, repo_type=repo_type, revision=revision, token=token)
File "/home/ubuntu/test_venv/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
return fn(*args, **kwargs)
File "/home/ubuntu/test_venv/lib/python3.10/site-packages/huggingface_hub/hf_api.py", line 2491, in repo_info
return method(
File "/home/ubuntu/test_venv/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
return fn(*args, **kwargs)
File "/home/ubuntu/test_venv/lib/python3.10/site-packages/huggingface_hub/hf_api.py", line 2366, in dataset_info
return DatasetInfo(**data)
File "/home/ubuntu/test_venv/lib/python3.10/site-packages/huggingface_hub/hf_api.py", line 799, in __init__
self.tags = kwargs.pop("tags")
KeyError: 'tags'
```
### Steps to reproduce the bug
```
1. huggingface-cli download --repo-type dataset gboleda/wikicorpus
```
### Expected behavior
There should be no error.
### Environment info
- `datasets` version: 2.19.1
- Platform: Linux-6.8.0-1015-aws-x86_64-with-glibc2.35
- Python version: 3.10.12
- `huggingface_hub` version: 0.23.5
- PyArrow version: 18.1.0
- Pandas version: 2.2.3
- `fsspec` version: 2024.3.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/5852 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5852/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5852/comments | https://api.github.com/repos/huggingface/datasets/issues/5852/events | https://github.com/huggingface/datasets/pull/5852 | 1,707,927,165 | PR_kwDODunzps5QZ1lj | 5,852 | Iterable torch formatting | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-05-12T16:48:49Z | 2023-06-13T16:04:05Z | 2023-06-13T15:57:05Z | MEMBER | null | null | null | Used the TorchFormatter to get torch tensors in iterable dataset with format set to "torch".
It uses the data from Arrow if possible, otherwise applies recursive_tensorize.
When set back to format_type=None, cast_to_python_objects is used.
requires https://github.com/huggingface/datasets/pull/5821
close https://github.com/huggingface/datasets/issues/5793 | {
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https://api.github.com/repos/huggingface/datasets/issues/6504 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6504/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6504/comments | https://api.github.com/repos/huggingface/datasets/issues/6504/events | https://github.com/huggingface/datasets/issues/6504 | 2,044,541,154 | I_kwDODunzps553Tji | 6,504 | Error Pushing to Hub | {
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} | ### Describe the bug
Error when trying to push a dataset in a special format to hub
### Steps to reproduce the bug
```
import datasets
from datasets import Dataset
dataset_dict = {
"filename": ["apple", "banana"],
"token": [[[1,2],[3,4]],[[1,2],[3,4]]],
"label": [0, 1],
}
dataset = Dataset.from_dict(dataset_dict)
dataset = dataset.cast_column("token", datasets.features.features.Array2D(shape=(2, 2),dtype="int16"))
dataset.push_to_hub("SequenceModel/imagenet_val_256")
```
Error:
```
...
ConstructorError: could not determine a constructor for the tag 'tag:yaml.org,2002:python/tuple'
in "<unicode string>", line 8, column 16:
shape: !!python/tuple
^
```
### Expected behavior
Dataset being pushed to hub
### Environment info
- `datasets` version: 2.15.0
- Platform: Linux-5.19.0-1022-gcp-x86_64-with-glibc2.35
- Python version: 3.11.5
- `huggingface_hub` version: 0.19.4
- PyArrow version: 14.0.1
- Pandas version: 2.1.4
- `fsspec` version: 2023.10.0 | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-07-04T18:26:55Z | 2022-07-05T15:19:52Z | 2022-07-05T15:08:21Z | CONTRIBUTOR | null | null | null | Fix #4612.
Apparently, newest `fsspec` versions do not allow access to attribute-based modules if they are not imported, such as `fsspec.async`.
Thus, @mariosasko suggested to add the missing part to the module import to allow for its access. | {
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https://api.github.com/repos/huggingface/datasets/issues/7006 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7006/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7006/comments | https://api.github.com/repos/huggingface/datasets/issues/7006/events | https://github.com/huggingface/datasets/issues/7006 | 2,379,581,543 | I_kwDODunzps6N1Yhn | 7,006 | CI is broken after ruff-0.5.0: E721 | {
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See: https://github.com/huggingface/datasets/actions/runs/9707641618/job/26793170961?pr=6983
> src/datasets/features/features.py:844:12: E721 Use `is` and `is not` for type comparisons, or `isinstance()` for isinstance checks | {
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https://api.github.com/repos/huggingface/datasets/issues/4797 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4797/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4797/comments | https://api.github.com/repos/huggingface/datasets/issues/4797/events | https://github.com/huggingface/datasets/pull/4797 | 1,330,000,998 | PR_kwDODunzps48uL-t | 4,797 | Torgo dataset creation | {
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"Hi @YingLi001, thanks for your proposal to add this dataset.\r\n\r\nHowever, now we add datasets directly to the Hub (instead of our GitHub repository). You have the instructions in our docs: \r\n- [Create a dataset loading script](https://huggingface.co/docs/datasets/dataset_script)\r\n- [Create a dataset card](h... | 2022-08-05T14:18:26Z | 2022-08-09T18:46:00Z | 2022-08-09T18:46:00Z | NONE | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6483 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6483/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6483/comments | https://api.github.com/repos/huggingface/datasets/issues/6483/events | https://github.com/huggingface/datasets/issues/6483 | 2,032,946,981 | I_kwDODunzps55LE8l | 6,483 | Iterable Dataset: rename column clashes with remove column | {
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"Column \"text\" doesn't exist anymore so you can't remove it",
"You can get the expected result by fixing typos in the snippet :)\r\n```python\r\nfrom datasets import load_dataset\r\n\r\n# load LS in streaming mode\r\ndataset = load_dataset(\"librispeech_asr\", \"clean\", split=\"validation\", streaming=True)\r\... | 2023-12-08T16:11:30Z | 2023-12-08T16:27:16Z | 2023-12-08T16:27:04Z | CONTRIBUTOR | null | null | {
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} | ### Describe the bug
Suppose I have a two iterable datasets, one with the features:
* `{"audio", "text", "column_a"}`
And the other with the features:
* `{"audio", "sentence", "column_b"}`
I want to combine both datasets using `interleave_datasets`, which requires me to unify the column names. I would typically do this by:
1. Renaming the common columns to the same name (e.g. `"text"` -> `"sentence"`)
2. Removing the unwanted columns (e.g. `"column_a"`, `"column_b"`)
However, the process of renaming and removing columns in an iterable dataset doesn't work, since we need to preserve the original text column, meaning we can't combine the datasets.
### Steps to reproduce the bug
```python
from datasets import load_dataset
# load LS in streaming mode
dataset = load_dataset("librispeech_asr", "clean", split="validation", streaming=True)
# check original features
dataset_features = dataset.features.keys()
print("Original features: ", dataset_features)
# rename "text" -> "sentence"
dataset = dataset.rename_column("text", "sentence")
# remove unwanted columns
COLUMNS_TO_KEEP = {"audio", "sentence"}
dataset = dataset.remove_columns(set(dataset_features - COLUMNS_TO_KEEP))
# stream first sample, should return "audio" and "sentence" columns
print(next(iter(dataset)))
```
Traceback:
```python
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
Cell In[5], line 17
14 COLUMNS_TO_KEEP = {"audio", "sentence"}
15 dataset = dataset.remove_columns(set(dataset_features - COLUMNS_TO_KEEP))
---> 17 print(next(iter(dataset)))
File ~/datasets/src/datasets/iterable_dataset.py:1353, in IterableDataset.__iter__(self)
1350 yield formatter.format_row(pa_table)
1351 return
-> 1353 for key, example in ex_iterable:
1354 if self.features:
1355 # `IterableDataset` automatically fills missing columns with None.
1356 # This is done with `_apply_feature_types_on_example`.
1357 example = _apply_feature_types_on_example(
1358 example, self.features, token_per_repo_id=self._token_per_repo_id
1359 )
File ~/datasets/src/datasets/iterable_dataset.py:652, in MappedExamplesIterable.__iter__(self)
650 yield from ArrowExamplesIterable(self._iter_arrow, {})
651 else:
--> 652 yield from self._iter()
File ~/datasets/src/datasets/iterable_dataset.py:729, in MappedExamplesIterable._iter(self)
727 if self.remove_columns:
728 for c in self.remove_columns:
--> 729 del transformed_example[c]
730 yield key, transformed_example
731 current_idx += 1
KeyError: 'text'
```
=> we see that `datasets` is looking for the column "text", even though we've renamed this to "sentence" and then removed the un-wanted "text" column from our dataset.
### Expected behavior
Should be able to rename and remove columns from iterable dataset.
### Environment info
- `datasets` version: 2.15.1.dev0
- Platform: macOS-13.5.1-arm64-arm-64bit
- Python version: 3.11.6
- `huggingface_hub` version: 0.19.4
- PyArrow version: 14.0.1
- Pandas version: 2.1.2
- `fsspec` version: 2023.9.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/6550 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6550/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6550/comments | https://api.github.com/repos/huggingface/datasets/issues/6550/events | https://github.com/huggingface/datasets/pull/6550 | 2,062,556,493 | PR_kwDODunzps5jD1OL | 6,550 | Multi gpu docs | {
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"Thanks @lhoestq . This is a very important fix for code to run on multiple GPUs. Otherw... | 2024-01-02T15:11:58Z | 2024-01-31T13:45:15Z | 2024-01-31T13:38:59Z | MEMBER | null | null | null | after discussions in https://github.com/huggingface/datasets/pull/6415 | {
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https://api.github.com/repos/huggingface/datasets/issues/6709 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6709/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6709/comments | https://api.github.com/repos/huggingface/datasets/issues/6709/events | https://github.com/huggingface/datasets/pull/6709 | 2,164,169,913 | PR_kwDODunzps5oc2Fg | 6,709 | set dev version | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-03-01T21:01:14Z | 2024-03-01T21:07:35Z | 2024-03-01T21:01:23Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7189 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7189/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7189/comments | https://api.github.com/repos/huggingface/datasets/issues/7189/events | https://github.com/huggingface/datasets/issues/7189 | 2,562,152,845 | I_kwDODunzps6Yt1mN | 7,189 | Audio preview in dataset viewer for audio array data without a path/filename | {
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} | ### Feature request
Huggingface has quite a comprehensive set of guides for [audio datasets](https://huggingface.co/docs/datasets/en/audio_dataset). It seems, however, all these guides assume the audio array data to be decoded/inserted into a HF dataset always originates from individual files. The [Audio-dataclass](https://github.com/huggingface/datasets/blob/3.0.1/src/datasets/features/audio.py#L20) appears designed with this assumption in mind. Looking at its source code it returns a dictionary with the keys `path`, `array` and `sampling_rate`.
However, sometimes users may have different pipelines where they themselves decode the audio array. This feature request has to do with wishing some clarification in guides on whether it is possible, and in such case how users can insert already decoded audio array data into datasets (pandas DataFrame, HF dataset or whatever) that are later saved as parquet, and still get a functioning audio preview in the dataset viewer.
Do I perhaps need to write a tempfile of my audio array slice to wav and capture the bytes object with `io.BytesIO` and pass that to `Audio()`?
### Motivation
I'm working with large audio datasets, and my pipeline reads (decodes) audio from larger files, and slices the relevant portions of audio from that larger file based on metadata I have available.
The pipeline is designed this way to avoid having to store multiple copies of data, and to avoid having to store tens of millions of small files.
I tried [test-uploading parquet files](https://huggingface.co/datasets/Lauler/riksdagen_test) where I store the audio array data of decoded slices of audio in an `audio` column with a dictionary with the keys `path`, `array` and `sampling_rate`. But I don't know the secret sauce of what the Huggingface Hub expects and requires to be able to display audio previews correctly.
### Your contribution
I could contribute a tool agnostic guide of creating HF audio datasets directly as parquet to the HF documentation if there is an interest. Provided you help me figure out the secret sauce of what the dataset viewer expects to display the preview correctly. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5866 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5866/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5866/comments | https://api.github.com/repos/huggingface/datasets/issues/5866/events | https://github.com/huggingface/datasets/issues/5866 | 1,710,496,993 | I_kwDODunzps5l9Bzh | 5,866 | Issue with Sequence features | {
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"Thanks for reporting! I've opened a PR with a fix."
] | 2023-05-15T17:13:29Z | 2023-05-26T11:57:17Z | 2023-05-26T11:57:17Z | NONE | null | null | {
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} | ### Describe the bug
Sequences features sometimes causes errors when the specified length is not -1
### Steps to reproduce the bug
```python
import numpy as np
from datasets import Features, ClassLabel, Sequence, Value, Dataset
feats = Features(**{'target': ClassLabel(names=[0, 1]),'x': Sequence(feature=Value(dtype='float64',id=None), length=2, id=None)})
Dataset.from_dict({"target": np.ones(2000).astype(int), "x": np.random.rand(2000,2)},features = feats).flatten_indices()
```
Throws:
```
TypeError: Couldn't cast array of type
fixed_size_list<item: double>[2]
to
Sequence(feature=Value(dtype='float64', id=None), length=2, id=None)
```
The same code works without any issues when `length = -1`
EDIT: The error seems to happen only when the length of the dataset is bigger than 1000 for some reason
### Expected behavior
No exception
### Environment info
- `datasets` version: 2.10.1
- Python version: 3.9.5
- PyArrow version: 11.0.0
- Pandas version: 1.4.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/5585 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5585/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5585/comments | https://api.github.com/repos/huggingface/datasets/issues/5585/events | https://github.com/huggingface/datasets/issues/5585 | 1,602,190,030 | I_kwDODunzps5ff3rO | 5,585 | Cache is not transportable | {
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"Hi ! No the cache is not transportable in general. It will work on a shared filesystem if you use the same python environment, but not across machines/os/environments.\r\n\r\nIn particular, reloading cached datasets does work, but reloading cached processed datasets (e.g. from `map`) may not work. This is because ... | 2023-02-28T00:53:06Z | 2023-02-28T21:26:52Z | 2023-02-28T21:26:52Z | NONE | null | null | {
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} | ### Describe the bug
I would like to share cache between two machines (a Windows host machine and a WSL instance).
I run most my code in WSL. I have just run out of space in the virtual drive. Rather than expand the drive size, I plan to move to cache to the host Windows machine, thereby sharing the downloads.
I'm hoping that I can just copy/paste the cache files, but I notice that a lot of the file names start with the path name, e.g. `_home_davidg_.cache_huggingface_datasets_conll2003_default-451...98.lock` where `home/davidg` is where the cache is in WSL.
This seems to suggest that the cache is not portable/cannot be centralised or shared. Is this the case, or are the files that start with path names not integral to the caching mechanism? Because copying the cache files _seems_ to work, but I'm not filled with confidence that something isn't going to break.
A related issue, when trying to load a dataset that should come from cache (running in WSL, pointing to cache on the Windows host) it seemed to work fine, but it still uses a WSL directory for `.cache\huggingface\modules\datasets_modules`. I see nothing in the docs about this, or how to point it to a different place.
I have asked a related question on the forum: https://discuss.huggingface.co/t/is-datasets-cache-operating-system-agnostic/32656
### Steps to reproduce the bug
View the cache directory in WSL/Windows.
### Expected behavior
Cache can be shared between (virtual) machines and be transportable.
It would be nice to have a simple way to say "Dear Hugging Face packages, please put ALL your cache in `blah/de/blah`" and have all the Hugging Face packages respect that single location.
### Environment info
```
- `datasets` version: 2.9.0
- Platform: Linux-5.10.102.1-microsoft-standard-WSL2-x86_64-with-glibc2.31
- Python version: 3.10.8
- PyArrow version: 11.0.0
- Pandas version: 1.5.3
- ``` | {
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https://api.github.com/repos/huggingface/datasets/issues/5870 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5870/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5870/comments | https://api.github.com/repos/huggingface/datasets/issues/5870/events | https://github.com/huggingface/datasets/issues/5870 | 1,712,156,282 | I_kwDODunzps5mDW56 | 5,870 | Behaviour difference between datasets.map and IterableDatasets.map | {
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"PS - some work is definitely needed for 'special cases' docs, not explanations, just usages of 'functions' under mixture of special cases, like a combination of custom databuilder + iterable dataset for large size + dynamic .map() application."
] | 2023-05-16T14:32:57Z | 2023-05-16T14:36:05Z | null | NONE | null | null | {
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} | ### Describe the bug
All the examples in all the docs mentioned throughout huggingface datasets correspond to datasets object, and not IterableDatasets object. At one point of time, they might have been in sync, but the code for datasets version >=2.9.0 is very different as compared to the docs.
I basically need to .map() a transform on images in an iterable dataset, which was made using a custom databuilder config.
This works very good in map-styles datasets, but the .map() fails in IterableDatasets, show behvaiour as such:
"pixel_values" key not found, KeyError in examples object/dict passed into transform function for map, which works fine with map style, even as batch.
In iterable style, the object/dict passed into map() paramter callable function is completely different as what is mentioned in all examples.
Please look into this. Thank you
My databuilder class is inherited as such:
def _info(self):
print ("Config: ",self.config.__dict__.keys())
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"labels": datasets.Sequence(datasets.Value("uint16")),
# "labels_name": datasets.Value("string"),
# "pixel_values": datasets.Array3D(shape=(3, 1280, 960), dtype="float32"),
"pixel_values": datasets.Array3D(shape=(1280, 960, 3), dtype="uint8"),
"image_s3_path": datasets.Value("string"),
}
),
supervised_keys=None,
homepage="none",
citation="",
)
def _split_generators(self, dl_manager):
records_train = list(db.mini_set.find({'split':'train'},{'image_s3_path':1, 'ocwen_template_name':1}))[:10000]
records_val = list(db.mini_set.find({'split':'val'},{'image_s3_path':1, 'ocwen_template_name':1}))[:1000]
# print (len(records),self.config.num_shards)
# shard_size_train = len(records_train)//self.config.num_shards
# sharded_records_train = [records_train[i:i+shard_size_train] for i in range(0,len(records_train),shard_size_train)]
# shard_size_val = len(records_val)//self.config.num_shards
# sharded_records_val = [records_val[i:i+shard_size_val] for i in range(0,len(records_val),shard_size_val)]
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN, gen_kwargs={"records":records_train} # passing list of records, for sharding to take over
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION, gen_kwargs={"records":records_val} # passing list of records, for sharding to take over
),
]
def _generate_examples(self, records):
# print ("Generating examples for [{}] shards".format(len(shards)))
# initiate_db_connection()
# records = list(db.mini_set.find({'split':split},{'image_s3_path':1, 'ocwen_template_name':1}))[:10]
id_ = 0
# for records in shards:
for i,rec in enumerate(records):
img_local_path = fetch_file(rec['image_s3_path'],self.config.buffer_dir)
# t = self.config.processor(Image.open(img_local_path), random_padding=True, return_tensors="np").pixel_values.squeeze()
# print (t.shape, type(t),type(t[0][0][0]))
# sys.exit()
pvs = np.array(Image.open(img_local_path).resize((1280,960))) # image object is wxh, so resize as per that, numpy array of it is hxwxc, transposing to cxwxh
# pvs = self.config.processor(Image.open(img_local_path), random_padding=True, return_tensors="np").pixel_values.astype(np.float16).squeeze()
# print (type(pvs[0][0][0]))
lblids = self.config.processor.tokenizer('<s_class>'+rec['ocwen_template_name']+'</s_class>'+'</s>', add_special_tokens=False, padding=False, truncation=False, return_tensors="np")["input_ids"].squeeze(0) # take padding later, as per batch collating
# print (len(lblids),type(lblids[0]))
# print (type(pvs),pvs.shape,type(pvs[0][0][0]), type(lblids))
yield id_, {"labels":lblids,"pixel_values":pvs,"image_s3_path":rec['image_s3_path']}
id_+=1
os.remove(img_local_path)
and I load it inside my trainer script as such
`ds = load_dataset("/tmp/DonutDS/dataset/", split="train", streaming=True) # iterable dataset, where .map() falls`
or also as
`ds = load_from_disk('/tmp/DonutDS/dataset/') #map style dataset`
Thank you to the team for having such a great library, and for this bug fix in advance!
### Steps to reproduce the bug
Above config can allow one to reproduce the said bug
### Expected behavior
.map() should show some consistency b/w map-style and iterable-style datasets, or atleast the docs should address iterable-style datasets behaviour and examples. I honestly do not figure the use of such docs.
### Environment info
datasets==2.9.0
transformers==4.26.0 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4542 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4542/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4542/comments | https://api.github.com/repos/huggingface/datasets/issues/4542/events | https://github.com/huggingface/datasets/issues/4542 | 1,280,269,445 | I_kwDODunzps5MT1yF | 4,542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | {
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"This has so much potential to be great! Also I think you tagged some poor random dude on the internet whose name is also Joao, lol, edited that for you! ",
"cc @sayakpaul here too, since he was interested in our new approaches to converting datasets!",
"Noted and I will look into the thread in detail tomorrow ... | 2022-06-22T14:42:00Z | 2022-10-11T08:45:45Z | null | MEMBER | null | null | {
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} | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_io` we could have something similar for `to_tf_dataset` if we provide sharded Feather files: https://www.tensorflow.org/io/api_docs/python/tfio/arrow/ArrowFeatherDataset
Feather is a format almost equivalent to the Arrow IPC Stream format we're using in `datasets`: Feather V2 is equivalent to Arrow IPC File format, which is an extension of the stream format (it has an extra footer). Therefore we could store datasets as Feather instead of Arrow IPC Stream format without breaking the whole library.
Here are a few points to explore
- [ ] check the performance of ArrowFeatherDataset in tf.data
- [ ] check what would change if we were to switch to Feather if needed, in particular check that those are fine: memory mapping, typing, writing, reading to python objects, etc.
We would also need to implement sharding when loading a dataset (this will be done anyway for #546)
cc @Rocketknight1 @gante feel free to comment in case I missed anything !
I'll share some files and scripts, so that we can benchmark performance of Feather files with tf.data | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5397 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5397/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5397/comments | https://api.github.com/repos/huggingface/datasets/issues/5397/events | https://github.com/huggingface/datasets/pull/5397 | 1,514,412,246 | PR_kwDODunzps5GYirs | 5,397 | Unpin pydantic test dependency | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2022-12-30T10:22:09Z | 2022-12-30T10:53:11Z | 2022-12-30T10:43:40Z | MEMBER | null | null | null | Once pydantic-1.10.3 has been yanked, we can unpin it: https://pypi.org/project/pydantic/1.10.3/
See reply by pydantic team https://github.com/pydantic/pydantic/issues/4885#issuecomment-1367819807
```
v1.10.3 has been yanked.
```
in response to spacy request: https://github.com/pydantic/pydantic/issues/4885#issuecomment-1367810049
```
On behalf of spacy-related packages: would it be possible for you to temporarily yank v1.10.3?
To address this and be compatible with v1.10.4, we'd have to release new versions of a whole series of packages and nearly everyone (including me) is currently on vacation. Even if v1.10.4 is released with a fix, pip would still back off to v1.10.3 for spacy, etc. because of its current pins for typing_extensions. If it could instead back off to v1.10.2, we'd have a bit more breathing room to make the updates on our end.
```
Close #5398.
| {
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https://api.github.com/repos/huggingface/datasets/issues/5505 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5505/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5505/comments | https://api.github.com/repos/huggingface/datasets/issues/5505/events | https://github.com/huggingface/datasets/issues/5505 | 1,571,720,814 | I_kwDODunzps5dro5u | 5,505 | PyTorch BatchSampler still loads from Dataset one-by-one | {
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"This change seems to come from a few months ago in the PyTorch side. That's good news and it means we may not need to pass a batch_sampler as soon as we add `Dataset.__getitems__` to get the optimal speed :)\r\n\r\nThanks for reporting ! Would you like to open a PR to add `__getitems__` and remove this outdated do... | 2023-02-06T01:14:55Z | 2023-02-19T18:27:30Z | 2023-02-19T18:27:30Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
In [the docs here](https://huggingface.co/docs/datasets/use_with_pytorch#use-a-batchsampler), it mentions the issue of the Dataset being read one-by-one, then states that using a BatchSampler resolves the issue.
I'm not sure if this is a mistake in the docs or the code, but it seems that the only way for a Dataset to be passed a list of indexes by PyTorch (instead of one index at a time) is to define a `__getitems__` method (note the plural) on the Dataset object, and since the HF Dataset doesn't have this, PyTorch executes [this line of code](https://github.com/pytorch/pytorch/blob/master/torch/utils/data/_utils/fetch.py#L58), reverting to fetching one-by-one.
### Steps to reproduce the bug
You can put a breakpoint in `Dataset.__getitem__()` or just print the args from there and see that it's called multiple times for a single `next(iter(dataloader))`, even when using the code from the docs:
```py
from torch.utils.data.sampler import BatchSampler, RandomSampler
batch_sampler = BatchSampler(RandomSampler(ds), batch_size=32, drop_last=False)
dataloader = DataLoader(ds, batch_sampler=batch_sampler)
```
### Expected behavior
The expected behaviour would be for it to fetch batches from the dataset, rather than one-by-one.
To demonstrate that there is room for improvement: once I have a HF dataset `ds`, if I just add this line:
```py
ds.__getitems__ = ds.__getitem__
```
...then the time taken to loop over the dataset improves considerably (for wikitext-103, from one minute to 13 seconds with batch size 32). Probably not a big deal in the grand scheme of things, but seems like an easy win.
### Environment info
- `datasets` version: 2.9.0
- Platform: Linux-5.10.102.1-microsoft-standard-WSL2-x86_64-with-glibc2.31
- Python version: 3.10.8
- PyArrow version: 10.0.1
- Pandas version: 1.5.3 | {
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https://api.github.com/repos/huggingface/datasets/issues/6503 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6503/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6503/comments | https://api.github.com/repos/huggingface/datasets/issues/6503/events | https://github.com/huggingface/datasets/pull/6503 | 2,043,847,591 | PR_kwDODunzps5iHgZf | 6,503 | Fix streaming xnli | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6503). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2023-12-15T14:40:57Z | 2023-12-15T14:51:06Z | 2023-12-15T14:44:47Z | MEMBER | null | null | null | This code was failing
```python
In [1]: from datasets import load_dataset
In [2]:
...: ds = load_dataset("xnli", "all_languages", split="test", streaming=True)
...:
...: sample_data = next(iter(ds))["premise"] # pick up one data
...: input_text = list(sample_data.values())
```
```
File ~/hf/datasets/src/datasets/features/translation.py:104, in TranslationVariableLanguages.encode_example(self, translation_dict)
102 return translation_dict
103 elif self.languages and set(translation_dict) - lang_set:
--> 104 raise ValueError(
105 f'Some languages in example ({", ".join(sorted(set(translation_dict) - lang_set))}) are not in valid set ({", ".join(lang_set)}).'
106 )
108 # Convert dictionary into tuples, splitting out cases where there are
109 # multiple translations for a single language.
110 translation_tuples = []
ValueError: Some languages in example (language, translation) are not in valid set (ur, fr, hi, sw, vi, el, de, th, en, tr, zh, ar, bg, ru, es).
```
because in streaming mode we expect features encode methods to be no-ops if the example is already encoded.
I fixed `TranslationVariableLanguages` to account for that | {
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https://api.github.com/repos/huggingface/datasets/issues/5511 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5511/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5511/comments | https://api.github.com/repos/huggingface/datasets/issues/5511/events | https://github.com/huggingface/datasets/issues/5511 | 1,575,851,768 | I_kwDODunzps5d7Zb4 | 5,511 | Creating a dummy dataset from a bigger one | {
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"Update `datasets` or downgrade `huggingface-hub` ;)\r\n\r\nThe `huggingface-hub` lib did a breaking change a few months ago, and you're using an old version of `datasets` that does't support it",
"Awesome thanks a lot! Everything works just fine with `datasets==2.9.0` :-) ",
"Getting same error with latest ver... | 2023-02-08T10:18:41Z | 2023-12-28T18:21:01Z | 2023-02-08T10:35:48Z | CONTRIBUTOR | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
I often want to create a dummy dataset from a bigger dataset for fast iteration when training. However, I'm having a hard time doing this especially when trying to upload the dataset to the Hub.
### Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("lambdalabs/pokemon-blip-captions")
dataset["train"] = dataset["train"].select(range(20))
dataset.push_to_hub("patrickvonplaten/dummy_image_data")
```
gives:
```
~/python_bin/datasets/arrow_dataset.py in _push_parquet_shards_to_hub(self, repo_id, split, private, token, branch, max_shard_size, embed_external_files)
4003 base_wait_time=2.0,
4004 max_retries=5,
-> 4005 max_wait_time=20.0,
4006 )
4007 return repo_id, split, uploaded_size, dataset_nbytes
~/python_bin/datasets/utils/file_utils.py in _retry(func, func_args, func_kwargs, exceptions, status_codes, max_retries, base_wait_time, max_wait_time)
328 while True:
329 try:
--> 330 return func(*func_args, **func_kwargs)
331 except exceptions as err:
332 if retry >= max_retries or (status_codes and err.response.status_code not in status_codes):
~/hf/lib/python3.7/site-packages/huggingface_hub/utils/_validators.py in _inner_fn(*args, **kwargs)
122 )
123
--> 124 return fn(*args, **kwargs)
125
126 return _inner_fn # type: ignore
TypeError: upload_file() got an unexpected keyword argument 'identical_ok'
In [2]:
```
### Expected behavior
I would have expected this to work. It's for me the most intuitive way of creating a dummy dataset.
### Environment info
```
- `datasets` version: 2.1.1.dev0
- Platform: Linux-4.19.0-22-cloud-amd64-x86_64-with-debian-10.13
- Python version: 3.7.3
- PyArrow version: 11.0.0
- Pandas version: 1.3.5
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/5366 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5366/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5366/comments | https://api.github.com/repos/huggingface/datasets/issues/5366/events | https://github.com/huggingface/datasets/pull/5366 | 1,498,530,851 | PR_kwDODunzps5FjSFl | 5,366 | ExamplesIterable fixes | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-12-15T14:23:05Z | 2022-12-15T14:44:47Z | 2022-12-15T14:41:45Z | MEMBER | null | null | null | fix typing and ExamplesIterable.shard_data_sources | {
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https://api.github.com/repos/huggingface/datasets/issues/4660 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4660/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4660/comments | https://api.github.com/repos/huggingface/datasets/issues/4660/events | https://github.com/huggingface/datasets/pull/4660 | 1,297,128,387 | PR_kwDODunzps47AYDq | 4,660 | Fix _resolve_single_pattern_locally on Windows with multiple drives | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Good catch ! Sorry I forgot (again) about windows paths when writing this x)"
] | 2022-07-07T09:57:30Z | 2022-07-07T17:03:36Z | 2022-07-07T16:52:07Z | MEMBER | null | null | null | Currently, when `_resolve_single_pattern_locally` is called from a different drive than the one in `pattern`, it raises an exception:
```
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
C:\hostedtoolcache\windows\Python\3.6.8\x64\lib\site-packages\datasets\io\parquet.py:35: in __init__
**kwargs,
C:\hostedtoolcache\windows\Python\3.6.8\x64\lib\site-packages\datasets\builder.py:287: in __init__
sanitize_patterns(data_files), base_path=base_path, use_auth_token=use_auth_token
C:\hostedtoolcache\windows\Python\3.6.8\x64\lib\site-packages\datasets\data_files.py:761: in from_local_or_remote
if not isinstance(patterns_for_key, DataFilesList)
C:\hostedtoolcache\windows\Python\3.6.8\x64\lib\site-packages\datasets\data_files.py:723: in from_local_or_remote
data_files = resolve_patterns_locally_or_by_urls(base_path, patterns, allowed_extensions)
C:\hostedtoolcache\windows\Python\3.6.8\x64\lib\site-packages\datasets\data_files.py:321: in resolve_patterns_locally_or_by_urls
for path in _resolve_single_pattern_locally(base_path, pattern, allowed_extensions):
C:\hostedtoolcache\windows\Python\3.6.8\x64\lib\site-packages\datasets\data_files.py:239: in _resolve_single_pattern_locally
for filepath in glob_iter
C:\hostedtoolcache\windows\Python\3.6.8\x64\lib\site-packages\datasets\data_files.py:242: in <listcomp>
os.path.relpath(filepath, base_path), os.path.relpath(pattern, base_path)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
path = 'C:\\Users\\runneradmin\\AppData\\Local\\Temp\\pytest-of-runneradmin\\pytest-0\\popen-gw0\\data6\\dataset.parquet'
start = '/'
...
E ValueError: path is on mount 'C:', start on mount 'D:'
```
This PR makes sure that `base_path` is in the same drive as `pattern`. | {
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https://api.github.com/repos/huggingface/datasets/issues/7480 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7480/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7480/comments | https://api.github.com/repos/huggingface/datasets/issues/7480/events | https://github.com/huggingface/datasets/issues/7480 | 2,950,315,214 | I_kwDODunzps6v2jzO | 7,480 | HF_DATASETS_CACHE ignored? | {
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"FWIW, it does eventually write to /tmp/roller/datasets when generating the final version.",
"Hey, I’d love to work on this issue but I am a beginner, can I work it with you?",
"Hi @lhoestq,\nI'd like to look into this issue but I'm still learning. Could you share any quick pointers on the HF_DATASETS_CACHE beh... | 2025-03-26T17:19:34Z | 2025-04-08T13:04:45Z | null | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
I'm struggling to get things to respect HF_DATASETS_CACHE.
Rationale: I'm on a system that uses NFS for homedir, so downloading to NFS is expensive, slow, and wastes valuable quota compared to local disk. Instead, it seems to rely mostly on HF_HUB_CACHE.
Current version: 3.2.1dev. In the process of testing 3.4.0
### Steps to reproduce the bug
[Currently writing using datasets 3.2.1dev. Will follow up with 3.4.0 results]
dump.py:
```python
from datasets import load_dataset
dataset = load_dataset("HuggingFaceFW/fineweb", name="sample-100BT", split="train")
```
Repro steps
```bash
# ensure no cache
$ mv ~/.cache/huggingface ~/.cache/huggingface.bak
$ export HF_DATASETS_CACHE=/tmp/roller/datasets
$ rm -rf ${HF_DATASETS_CACHE}
$ env | grep HF | grep -v TOKEN
HF_DATASETS_CACHE=/tmp/roller/datasets
$ python dump.py
# (omitted for brevity)
# (while downloading)
$ du -hcs ~/.cache/huggingface/hub
18G hub
18G total
# (after downloading)
$ du -hcs ~/.cache/huggingface/hub
```
It's a shame because datasets supports s3 (which I could really use right now) but hub does not.
### Expected behavior
* ~/.cache/huggingface/hub stays empty
* /tmp/roller/datasets becomes full of stuff
### Environment info
[Currently writing using datasets 3.2.1dev. Will follow up with 3.4.0 results] | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4893 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4893/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4893/comments | https://api.github.com/repos/huggingface/datasets/issues/4893/events | https://github.com/huggingface/datasets/issues/4893 | 1,350,655,674 | I_kwDODunzps5QgV66 | 4,893 | Oversampling strategy for iterable datasets in `interleave_datasets` | {
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"Hi @lhoestq,\r\nI plunged into the code and it should be manageable for me to work on it!\r\n#take\r\n\r\nAlso, setting `d1`, `d2` and `d3` as you did raised a `SyntaxError: 'yield' inside list comprehension` for me, on Python 3.8.10.\r\nThe following snippet works for me though:\r\n```\r\nd1 = IterableDataset(Exa... | 2022-08-25T10:06:55Z | 2022-10-03T12:37:46Z | 2022-10-03T12:37:46Z | MEMBER | null | null | {
"completed": 0,
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} | In https://github.com/huggingface/datasets/pull/4831 @ylacombe added an oversampling strategy for `interleave_datasets`. However right now it doesn't work for datasets loaded using `load_dataset(..., streaming=True)`, which are `IterableDataset` objects.
It would be nice to expand `interleave_datasets` for iterable datasets as well to support this oversampling strategy
```python
>>> from datasets.iterable_dataset import IterableDataset, ExamplesIterable
>>> d1 = IterableDataset(ExamplesIterable(lambda: [(yield i, {"a": i}) for i in [0, 1, 2]], {}))
>>> d2 = IterableDataset(ExamplesIterable(lambda: [(yield i, {"a": i}) for i in [10, 11, 12, 13]], {}))
>>> d3 = IterableDataset(ExamplesIterable(lambda: [(yield i, {"a": i}) for i in [20, 21, 22, 23, 24]], {}))
>>> dataset = interleave_datasets([d1, d2, d3]) # is supported
>>> [x["a"] for x in dataset]
[0, 10, 20, 1, 11, 21, 2, 12, 22]
>>> dataset = interleave_datasets([d1, d2, d3], stopping_strategy="all_exhausted") # is not supported yet
>>> [x["a"] for x in dataset]
[0, 10, 20, 1, 11, 21, 2, 12, 22, 0, 13, 23, 1, 0, 24]
```
This can be implemented by adding the strategy to both `CyclingMultiSourcesExamplesIterable` and `RandomlyCyclingMultiSourcesExamplesIterable` used in `_interleave_iterable_datasets` in `iterable_dataset.py`
I would be happy to share some guidance if anyone would like to give it a shot :) | {
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https://api.github.com/repos/huggingface/datasets/issues/6289 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6289/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6289/comments | https://api.github.com/repos/huggingface/datasets/issues/6289/events | https://github.com/huggingface/datasets/pull/6289 | 1,935,628,506 | PR_kwDODunzps5cZiay | 6,289 | testing doc-builder | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-10-10T15:17:29Z | 2023-10-13T08:57:14Z | 2023-10-13T08:56:48Z | NONE | null | null | null | testing https://github.com/huggingface/doc-builder/pull/426 | {
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https://api.github.com/repos/huggingface/datasets/issues/5201 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5201/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5201/comments | https://api.github.com/repos/huggingface/datasets/issues/5201/events | https://github.com/huggingface/datasets/pull/5201 | 1,435,881,554 | PR_kwDODunzps5CM0zn | 5,201 | Do not sort splits in dataset info | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"It would be coherent with https://github.com/huggingface/datasets-server/issues/614#issuecomment-1290534153",
"I think we started working on this issue nearly at the same time... :sweat_smile: \r\n- CI was fixed with this: https://... | 2022-11-04T10:47:21Z | 2022-11-04T14:47:37Z | 2022-11-04T14:45:09Z | CONTRIBUTOR | null | null | null | I suggest not to sort splits by their names in dataset_info in README so that they are displayed in the order specified in the loading script. Otherwise `test` split is displayed first, see this repo: https://huggingface.co/datasets/paws
What do you think?
But I added sorting in tests to fix CI (for the same dataset). | {
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https://api.github.com/repos/huggingface/datasets/issues/5267 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5267/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5267/comments | https://api.github.com/repos/huggingface/datasets/issues/5267/events | https://github.com/huggingface/datasets/pull/5267 | 1,455,466,464 | PR_kwDODunzps5DOlFR | 5,267 | Fix `max_shard_size` docs | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-11-18T16:55:22Z | 2022-11-18T17:28:58Z | 2022-11-18T17:25:27Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7504 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7504/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7504/comments | https://api.github.com/repos/huggingface/datasets/issues/7504/events | https://github.com/huggingface/datasets/issues/7504 | 2,979,410,641 | I_kwDODunzps6xljLR | 7,504 | BuilderConfig ParquetConfig(...) doesn't have a 'use_auth_token' key. | {
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"I encountered the same error, have you resolved it?",
"Hi ! `use_auth_token` has been deprecated and removed some time ago. You should use `token` instead in `load_dataset()`"
] | 2025-04-08T10:55:03Z | 2025-04-15T12:36:28Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
Trying to run the following fine-tuning script (based on this page [here](https://github.com/huggingface/instruction-tuned-sd)):
```
! accelerate launch /content/instruction-tuned-sd/finetune_instruct_pix2pix.py \
--pretrained_model_name_or_path=${MODEL_ID} \
--dataset_name=${DATASET_NAME} \
--use_ema \
--enable_xformers_memory_efficient_attention \
--resolution=512 --random_flip \
--train_batch_size=2 --gradient_accumulation_steps=4 --gradient_checkpointing \
--max_train_steps=500 \
--checkpointing_steps=25 --checkpoints_total_limit=1 \
--learning_rate=5e-05 --max_grad_norm=1 --lr_warmup_steps=20 \
--conditioning_dropout_prob=0.1 \
--mixed_precision=fp16 \
--seed=42 \
--output_dir=${OUTPUT_DIR} \
--original_image_column=before \
--edit_prompt=prompt \
--edited_image=after
```
but I keep getting the following error:
```
Traceback (most recent call last):
File "/content/instruction-tuned-sd/finetune_instruct_pix2pix.py", line 1137, in <module>
main()
File "/content/instruction-tuned-sd/finetune_instruct_pix2pix.py", line 652, in main
dataset = load_dataset(
^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/load.py", line 2129, in load_dataset
builder_instance = load_dataset_builder(
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/load.py", line 1886, in load_dataset_builder
builder_instance: DatasetBuilder = builder_cls(
^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/builder.py", line 342, in __init__
self.config, self.config_id = self._create_builder_config(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/builder.py", line 590, in _create_builder_config
raise ValueError(f"BuilderConfig {builder_config} doesn't have a '{key}' key.")
ValueError: BuilderConfig ParquetConfig(name='default', version=0.0.0, data_dir=None, data_files={'train': ['data/train-*']}, description=None, batch_size=None, columns=None, features=None, filters=None) doesn't have a 'use_auth_token' key.
Traceback (most recent call last):
File "/usr/local/bin/accelerate", line 10, in <module>
sys.exit(main())
^^^^^^
```
Any ideas? `datasets` version should be `3.2.0`.
### Steps to reproduce the bug
Just running the script above.
### Expected behavior
No errors
### Environment info
Python 3.11.11
datasets==3.2.0 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4986 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4986/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4986/comments | https://api.github.com/repos/huggingface/datasets/issues/4986/events | https://github.com/huggingface/datasets/pull/4986 | 1,375,895,035 | PR_kwDODunzps4_GNSd | 4,986 | [doc] Fix broken snippet that had too many quotes | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Spent the day familiarising myself with the huggingface line of products, and happened to run into some small issues here and there. Magically, I've found exactly one small issue in `transformers`, one in `accelerate` and now one in ... | 2022-09-16T12:41:07Z | 2022-09-16T22:12:21Z | 2022-09-16T17:32:14Z | MEMBER | null | null | null | Hello!
### Pull request overview
* Fix broken snippet in https://huggingface.co/docs/datasets/main/en/process that has too many quotes
### Details
The snippet in question can be found here: https://huggingface.co/docs/datasets/main/en/process#map
This screenshot shows the issue, there is a quote too many, causing the snippet to be colored incorrectly:
The change speaks for itself.
Thank you for the detailed documentation, by the way.
- Tom Aarsen
| {
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https://api.github.com/repos/huggingface/datasets/issues/7488 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7488/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7488/comments | https://api.github.com/repos/huggingface/datasets/issues/7488/events | https://github.com/huggingface/datasets/pull/7488 | 2,956,559,358 | PR_kwDODunzps6QlLmn | 7,488 | Support underscore int read instruction | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7488). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"you rock, Quentin - thank you!"
] | 2025-03-28T16:01:15Z | 2025-03-28T16:20:44Z | 2025-03-28T16:20:43Z | MEMBER | null | null | null | close https://github.com/huggingface/datasets/issues/7481 | {
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https://api.github.com/repos/huggingface/datasets/issues/6148 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6148/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6148/comments | https://api.github.com/repos/huggingface/datasets/issues/6148/events | https://github.com/huggingface/datasets/pull/6148 | 1,849,524,683 | PR_kwDODunzps5X3oqv | 6,148 | Ignore parallel warning in map_nested | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-08-14T10:43:41Z | 2023-08-17T08:54:06Z | 2023-08-17T08:43:58Z | MEMBER | null | null | null | This warning message was shown every time you pass num_proc to `load_dataset` because of `map_nested`
```
parallel_map is experimental and might be subject to breaking changes in the future
```
This PR removes it for `map_nested`. If someone uses another parallel backend they're already warned when `parallel_backend` is called anyway | {
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https://api.github.com/repos/huggingface/datasets/issues/6055 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6055/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6055/comments | https://api.github.com/repos/huggingface/datasets/issues/6055/events | https://github.com/huggingface/datasets/issues/6055 | 1,813,524,145 | I_kwDODunzps5sGC6x | 6,055 | Fix host URL in The Pile datasets | {
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} | [] | open | false | null | [] | null | [] | 2023-07-20T09:08:52Z | 2023-07-20T09:09:37Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
In #3627 and #5543, you tried to fix the host URL in The Pile datasets. But both URLs are not working now:
`HTTPError: 404 Client Error: Not Found for URL: https://the-eye.eu/public/AI/pile_preliminary_components/PUBMED_title_abstracts_2019_baseline.jsonl.zst`
And
`ConnectTimeout: HTTPSConnectionPool(host='mystic.the-eye.eu', port=443): Max retries exceeded with url: /public/AI/pile_preliminary_components/PUBMED_title_abstracts_2019_baseline.jsonl.zst (Caused by ConnectTimeoutError(, 'Connection to mystic.the-eye.eu timed out. (connect timeout=10.0)'))`
### Steps to reproduce the bug
```
from datasets import load_dataset
# This takes a few minutes to run, so go grab a tea or coffee while you wait :)
data_files = "https://mystic.the-eye.eu/public/AI/pile_preliminary_components/PUBMED_title_abstracts_2019_baseline.jsonl.zst"
pubmed_dataset = load_dataset("json", data_files=data_files, split="train")
pubmed_dataset
```
Result:
`ConnectTimeout: HTTPSConnectionPool(host='mystic.the-eye.eu', port=443): Max retries exceeded with url: /public/AI/pile_preliminary_components/PUBMED_title_abstracts_2019_baseline.jsonl.zst (Caused by ConnectTimeoutError(, 'Connection to mystic.the-eye.eu timed out. (connect timeout=10.0)'))`
And
```
from datasets import load_dataset
# This takes a few minutes to run, so go grab a tea or coffee while you wait :)
data_files = "https://the-eye.eu/public/AI/pile_preliminary_components/PUBMED_title_abstracts_2019_baseline.jsonl.zst"
pubmed_dataset = load_dataset("json", data_files=data_files, split="train")
pubmed_dataset
```
Result:
`HTTPError: 404 Client Error: Not Found for URL: https://the-eye.eu/public/AI/pile_preliminary_components/PUBMED_title_abstracts_2019_baseline.jsonl.zst`
### Expected behavior
Downloading as normal.
### Environment info
Environment info
`datasets` version: 2.9.0
Platform: Windows
Python version: 3.9.13
| null | {
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https://api.github.com/repos/huggingface/datasets/issues/5465 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5465/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5465/comments | https://api.github.com/repos/huggingface/datasets/issues/5465/events | https://github.com/huggingface/datasets/issues/5465 | 1,557,510,618 | I_kwDODunzps5c1bna | 5,465 | audiofolder creates empty dataset even though the dataset passed in follows the correct structure | {
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} | [] | closed | false | null | [] | null | [] | 2023-01-26T01:45:45Z | 2023-01-26T08:48:45Z | 2023-01-26T08:48:45Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
The structure of my dataset folder called "my_dataset" is : data metadata.csv
The data folder consists of all mp3 files and metadata.csv consist of file locations like 'data/...mp3 and transcriptions. There's 400+ mp3 files and corresponding transcriptions for my dataset.
When I run the following:
ds = load_dataset("audiofolder", data_dir="my_dataset")
I get:
Using custom data configuration default-...
Downloading and preparing dataset audiofolder/default to /...
Downloading data files: 0%| | 0/2 [00:00<?, ?it/s]
Downloading data files: 0it [00:00, ?it/s]
Extracting data files: 0it [00:00, ?it/s]
Generating train split: 0 examples [00:00, ? examples/s]
Dataset audiofolder downloaded and prepared to /.... Subsequent calls will reuse this data.
0%| | 0/1 [00:00<?, ?it/s]
DatasetDict({
train: Dataset({
features: ['audio', 'transcription'],
num_rows: 1
})
})
### Steps to reproduce the bug
Create a dataset folder called 'my_dataset' with a subfolder called 'data' that has mp3 files. Also, create metadata.csv that has file locations like 'data/...mp3' and their corresponding transcription.
Run:
ds = load_dataset("audiofolder", data_dir="my_dataset")
### Expected behavior
It should generate a dataset with numerous rows.
### Environment info
Run on Jupyter notebook | {
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https://api.github.com/repos/huggingface/datasets/issues/5603 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5603/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5603/comments | https://api.github.com/repos/huggingface/datasets/issues/5603/events | https://github.com/huggingface/datasets/pull/5603 | 1,607,143,509 | PR_kwDODunzps5LJZzG | 5,603 | Don't compute checksums if not necessary in `datasets-cli test` | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-03-02T16:42:39Z | 2023-03-03T15:45:32Z | 2023-03-03T15:38:28Z | MEMBER | null | null | null | we only need them if there exists a `dataset_infos.json` | {
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https://api.github.com/repos/huggingface/datasets/issues/5826 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5826/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5826/comments | https://api.github.com/repos/huggingface/datasets/issues/5826/events | https://github.com/huggingface/datasets/pull/5826 | 1,698,155,751 | PR_kwDODunzps5P5FYZ | 5,826 | Support working_dir in from_spark | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Added env var",
"@lhoestq would you or another maintainer be able to review please? :)",
"I removed the env var",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!<... | 2023-05-05T20:22:40Z | 2023-05-25T17:45:54Z | 2023-05-25T08:46:15Z | CONTRIBUTOR | null | null | null | Accept `working_dir` as an argument to `Dataset.from_spark`. Setting a non-NFS working directory for Spark workers to materialize to will improve write performance. | {
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https://api.github.com/repos/huggingface/datasets/issues/5596 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5596/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5596/comments | https://api.github.com/repos/huggingface/datasets/issues/5596/events | https://github.com/huggingface/datasets/issues/5596 | 1,604,919,993 | I_kwDODunzps5fqSK5 | 5,596 | [TypeError: Couldn't cast array of type] Can only load a subset of the dataset | {
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"Apparently some JSON objects have a `\"labels\"` field. Since this field is not present in every object, you must specify all the fields types in the README.md\r\n\r\nEDIT: actually specifying the feature types doesn’t solve the issue, it raises an error because “labels” is missing in the data",
"We've updated t... | 2023-03-01T12:53:08Z | 2023-12-05T03:22:00Z | 2023-03-02T11:12:11Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
I'm trying to load this [dataset](https://huggingface.co/datasets/bigcode-data/the-stack-gh-issues) which consists of jsonl files and I get the following error:
```
casted_values = _c(array.values, feature[0])
File "/opt/conda/lib/python3.7/site-packages/datasets/table.py", line 1839, in wrapper
return func(array, *args, **kwargs)
File "/opt/conda/lib/python3.7/site-packages/datasets/table.py", line 2132, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{feature}")
TypeError: Couldn't cast array of type
struct<type: string, action: string, datetime: timestamp[s], author: string, title: string, description: string, comment_id: int64, comment: string, labels: list<item: string>>
to
{'type': Value(dtype='string', id=None), 'action': Value(dtype='string', id=None), 'datetime': Value(dtype='timestamp[s]', id=None), 'author': Value(dtype='string', id=None), 'title': Value(dtype='string', id=None), 'description': Value(dtype='string', id=None), 'comment_id': Value(dtype='int64', id=None), 'comment': Value(dtype='string', id=None)}
```
But I can succesfully load a subset of the dataset, for example this works:
```python
ds = load_dataset('bigcode-data/the-stack-gh-issues', split="train", data_files=[f"data/data-{x}.jsonl" for x in range(10)])
```
and `ds.features` returns:
```
{'repo': Value(dtype='string', id=None),
'org': Value(dtype='string', id=None),
'issue_id': Value(dtype='int64', id=None),
'issue_number': Value(dtype='int64', id=None),
'pull_request': {'user_login': Value(dtype='string', id=None),
'repo': Value(dtype='string', id=None),
'number': Value(dtype='int64', id=None)},
'events': [{'type': Value(dtype='string', id=None),
'action': Value(dtype='string', id=None),
'datetime': Value(dtype='timestamp[s]', id=None),
'author': Value(dtype='string', id=None),
'title': Value(dtype='string', id=None),
'description': Value(dtype='string', id=None),
'comment_id': Value(dtype='int64', id=None),
'comment': Value(dtype='string', id=None)}]}
```
So I'm not sure if there's an issue with just some of the files. Grateful if you have any suggestions to fix the issue.
Side note:
I saw this related [issue](https://github.com/huggingface/datasets/issues/3637) and tried to write a loading script to have `events` as a `Sequence` and not `list` [here](https://huggingface.co/datasets/bigcode-data/the-stack-gh-issues/blob/main/loading.py) (the script was renamed). It worked with a subset locally but doesn't for the remote dataset it can't find https://huggingface.co/datasets/bigcode-data/the-stack-gh-issues/resolve/main/data.
### Steps to reproduce the bug
```python
from datasets import load_dataset
ds = load_dataset('bigcode-data/the-stack-gh-issues', split="train")
```
### Expected behavior
Load the entire dataset succesfully.
### Environment info
- `datasets` version: 2.10.1
- Platform: Linux-4.19.0-23-cloud-amd64-x86_64-with-debian-10.13
- Python version: 3.7.12
- PyArrow version: 9.0.0
- Pandas version: 1.3.4 | {
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https://api.github.com/repos/huggingface/datasets/issues/5468 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5468/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5468/comments | https://api.github.com/repos/huggingface/datasets/issues/5468/events | https://github.com/huggingface/datasets/issues/5468 | 1,558,066,625 | I_kwDODunzps5c3jXB | 5,468 | Allow opposite of remove_columns on Dataset and DatasetDict | {
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"default": true... | closed | false | null | [] | null | [
"Hi! I agree it would be nice to have a method like that. Instead of `keep_columns`, we can name it `select_columns` to be more aligned with PyArrow's naming convention (`pa.Table.select`).",
"Hi, I am a newbie to open source and would like to contribute. @mariosasko can I take up this issue ?",
"Hey, I also wa... | 2023-01-26T12:28:09Z | 2023-02-13T09:59:38Z | 2023-02-13T09:59:38Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Feature request
In this blog post https://huggingface.co/blog/audio-datasets, I noticed the following code:
```python
COLUMNS_TO_KEEP = ["text", "audio"]
all_columns = gigaspeech["train"].column_names
columns_to_remove = set(all_columns) - set(COLUMNS_TO_KEEP)
gigaspeech = gigaspeech.remove_columns(columns_to_remove)
```
This kind of thing happens a lot when you don't need to keep all columns from the dataset. It would be more convenient (and less error prone) if you could just write:
```python
gigaspeech = gigaspeech.keep_columns(["text", "audio"])
```
Internally, `keep_columns` could still call `remove_columns`, but it expresses more clearly what the user's intent is.
### Motivation
Less code to write for the user of the dataset.
### Your contribution
- | {
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https://api.github.com/repos/huggingface/datasets/issues/4706 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4706/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4706/comments | https://api.github.com/repos/huggingface/datasets/issues/4706/events | https://github.com/huggingface/datasets/pull/4706 | 1,308,198,454 | PR_kwDODunzps47lNBg | 4,706 | Fix empty examples in xtreme dataset for bucc18 config | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"I guess the report link is this instead: https://huggingface.co/datasets/xtreme/discussions/1"
] | 2022-07-18T16:22:46Z | 2022-07-19T06:41:14Z | 2022-07-19T06:29:17Z | MEMBER | null | null | null | As reported in https://huggingface.co/muibk, there are empty examples in xtreme/bucc18.de
I applied your fix @mustaszewski
I also used a dict to make the dataset generation much faster | {
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https://api.github.com/repos/huggingface/datasets/issues/7476 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7476/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7476/comments | https://api.github.com/repos/huggingface/datasets/issues/7476/events | https://github.com/huggingface/datasets/pull/7476 | 2,946,997,924 | PR_kwDODunzps6QEbmO | 7,476 | Priotitize json | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7476). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2025-03-25T15:44:31Z | 2025-03-25T15:47:00Z | 2025-03-25T15:45:00Z | MEMBER | null | null | null | `datasets` should load the JSON data in https://huggingface.co/datasets/facebook/natural_reasoning, not the PDF | {
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https://api.github.com/repos/huggingface/datasets/issues/5321 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5321/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5321/comments | https://api.github.com/repos/huggingface/datasets/issues/5321/events | https://github.com/huggingface/datasets/pull/5321 | 1,471,430,667 | PR_kwDODunzps5EEOhE | 5,321 | Fix loading from HF GCP cache | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"> Do you know why this stopped working?\r\n\r\nIt comes from the changes in https://github.com/huggingface/datasets/pull/5107/files#diff-355ae5c229f95f86895404b72378ecd6e966c41cbeebb674af6fe6e9611bc126"
] | 2022-12-01T14:39:06Z | 2022-12-01T16:10:09Z | 2022-12-01T16:07:02Z | MEMBER | null | null | null | As reported in https://discuss.huggingface.co/t/error-loading-wikipedia-dataset/26599/4 it's not possible to download a cached version of Wikipedia from the HF GCP cache
I fixed it and added an integration test (runs in 10sec) | {
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https://api.github.com/repos/huggingface/datasets/issues/6103 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6103/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6103/comments | https://api.github.com/repos/huggingface/datasets/issues/6103/events | https://github.com/huggingface/datasets/pull/6103 | 1,828,515,165 | PR_kwDODunzps5Ww2gV | 6,103 | Set dev version | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6103). All of your documentation changes will be reflected on that endpoint.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchma... | 2023-07-31T06:44:05Z | 2023-07-31T06:55:58Z | 2023-07-31T06:45:41Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5609 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5609/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5609/comments | https://api.github.com/repos/huggingface/datasets/issues/5609/events | https://github.com/huggingface/datasets/issues/5609 | 1,610,062,862 | I_kwDODunzps5f95wO | 5,609 | `load_from_disk` vs `load_dataset` performance. | {
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"Hi! We've recently made some improvements to `save_to_disk`/`list_to_disk` (100x faster in some scenarios), so it would help if you could install `datasets` directly from `main` (`pip install git+https://github.com/huggingface/datasets.git`) and re-run the \"benchmark\".",
"Great to hear! I'll give it a try when... | 2023-03-05T05:27:15Z | 2023-07-13T18:48:05Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
I have downloaded `openwebtext` (~12GB) and filtered out a small amount of junk (it's still huge). Now, I would like to use this filtered version for future work. It seems I have two choices:
1. Use `load_dataset` each time, relying on the cache mechanism, and re-run my filtering.
2. `save_to_disk` and then use `load_from_disk` to load the filtered version.
The performance of these two approaches is wildly different:
* Using `load_dataset` takes about 20 seconds to load the dataset, and a few seconds to re-filter (thanks to the brilliant filter/map caching)
* Using `load_from_disk` takes 14 minutes! And the second time I tried, the session just crashed (on a machine with 32GB of RAM)
I don't know if you'd call this a bug, but it seems like there shouldn't need to be two methods to load from disk, or that they should not take such wildly different amounts of time, or that one should not crash. Or maybe that the docs could offer some guidance about when to pick which method and why two methods exist, or just how do most people do it?
Something I couldn't work out from reading the docs was this: can I modify a dataset from the hub, save it (locally) and use `load_dataset` to load it? This [post seemed to suggest that the answer is no](https://discuss.huggingface.co/t/save-and-load-datasets/9260).
### Steps to reproduce the bug
See above
### Expected behavior
Load times should be about the same.
### Environment info
- `datasets` version: 2.9.0
- Platform: Linux-5.10.102.1-microsoft-standard-WSL2-x86_64-with-glibc2.31
- Python version: 3.10.8
- PyArrow version: 11.0.0
- Pandas version: 1.5.3 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6628 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6628/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6628/comments | https://api.github.com/repos/huggingface/datasets/issues/6628/events | https://github.com/huggingface/datasets/pull/6628 | 2,105,760,502 | PR_kwDODunzps5lVxXU | 6,628 | Make CLI test support multi-processing | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6628). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"@huggingface/datasets, feel free to review this PR so that it can be included in the ne... | 2024-01-29T15:30:09Z | 2024-02-05T10:29:20Z | 2024-02-05T10:23:13Z | MEMBER | null | null | null | Support passing `--num_proc` to CLI test.
This was really useful recently to run the command on `pubmed`: https://huggingface.co/datasets/pubmed/discussions/11 | {
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https://api.github.com/repos/huggingface/datasets/issues/7165 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7165/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7165/comments | https://api.github.com/repos/huggingface/datasets/issues/7165/events | https://github.com/huggingface/datasets/pull/7165 | 2,544,972,541 | PR_kwDODunzps58fva1 | 7,165 | fix increase_load_count | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7165). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"I tested a few load_dataset and they do show up in download stats now",
"Thanks for h... | 2024-09-24T10:14:40Z | 2024-09-24T17:31:07Z | 2024-09-24T13:48:00Z | MEMBER | null | null | null | it was failing since 3.0 and therefore not updating download counts on HF or in our dashboard | {
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https://api.github.com/repos/huggingface/datasets/issues/4789 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4789/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4789/comments | https://api.github.com/repos/huggingface/datasets/issues/4789/events | https://github.com/huggingface/datasets/pull/4789 | 1,328,409,253 | PR_kwDODunzps48o3Kk | 4,789 | Update doc upload_dataset.mdx | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-04T10:24:00Z | 2022-09-09T16:37:10Z | 2022-09-09T16:34:58Z | NONE | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6216 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6216/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6216/comments | https://api.github.com/repos/huggingface/datasets/issues/6216/events | https://github.com/huggingface/datasets/pull/6216 | 1,883,492,703 | PR_kwDODunzps5Zp8al | 6,216 | Release: 2.13.2 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-09-06T08:15:32Z | 2023-09-06T08:52:18Z | 2023-09-06T08:22:43Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7300 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7300/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7300/comments | https://api.github.com/repos/huggingface/datasets/issues/7300/events | https://github.com/huggingface/datasets/pull/7300 | 2,701,424,320 | PR_kwDODunzps6Dcba8 | 7,300 | fix: update elasticsearch version | {
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"May I request a review @lhoestq",
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7300). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2024-11-28T09:14:21Z | 2024-12-03T14:36:56Z | 2024-12-03T14:24:42Z | CONTRIBUTOR | null | null | null | This should fix the `test_py311 (windows latest, deps-latest` errors.
```
=========================== short test summary info ===========================
ERROR tests/test_search.py - AttributeError: `np.float_` was removed in the NumPy 2.0 release. Use `np.float64` instead.
ERROR tests/test_search.py - AttributeError: `np.float_` was removed in the NumPy 2.0 release. Use `np.float64` instead.
===== 2822 passed, 54 skipped, 10 warnings, 2 errors in 373.36s (0:06:13) =====
Error: Process completed with exit code 1.
```
The elasticsearch version used is `elasticsearch==7.9.1`, which is 4 years old and uses the removed `numpy.float_`.
elasticsearch fixed this in [https://github.com/elastic/elasticsearch-py/pull/2551](https://github.com/elastic/elasticsearch-py/pull/2551) and released in 8.15.0 (August 2024) and 7.17.12 (September 2024).
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https://api.github.com/repos/huggingface/datasets/issues/4647 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4647/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4647/comments | https://api.github.com/repos/huggingface/datasets/issues/4647/events | https://github.com/huggingface/datasets/issues/4647 | 1,296,311,270 | I_kwDODunzps5NRCPm | 4,647 | Add Reddit dataset | {
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} | ## Adding a Dataset
- **Name:** *Reddit comments (2015-2018)*
- **Description:** *Reddit is an American social news aggregation website, where users can post links, and take part in discussions on these posts. These threaded discussions provide a large corpus, which is converted into a conversational dataset using the tools in this directory.*
- **Paper:** *https://arxiv.org/abs/1904.06472*
- **Data:** *https://github.com/PolyAI-LDN/conversational-datasets/tree/master/reddit*
- **Motivation:** *Dataset for training and evaluating models of conversational response*
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https://api.github.com/repos/huggingface/datasets/issues/6201 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6201/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6201/comments | https://api.github.com/repos/huggingface/datasets/issues/6201/events | https://github.com/huggingface/datasets/pull/6201 | 1,875,256,775 | PR_kwDODunzps5ZOVbV | 6,201 | Fix to_json ValueError and remove pandas pin | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-08-31T10:38:08Z | 2023-09-05T11:07:07Z | 2023-09-05T10:58:21Z | MEMBER | null | null | null | This PR fixes the root cause of the issue:
- #6197
This PR also removes the temporary pin of `pandas` introduced by:
- #6200
Note that for orient in ['records', 'values'], index value is ignored but
- in `pandas` < 2.1.0, a ValueError is raised if not index and orient not in ['split', 'table']
- for orient = 'records', we need index = True
- default index value is True
- in `pandas` = 2.1.0, a ValueError is raised if index is True and orient in ['records', 'values']
- for orient = 'records', we need index = False or None
- default index value is None
This PR fixes the issue by not passing index and thus using default index value (valid for all pandas versions), unless orient is 'split' or 'table' (where we pass index = False, as it was done before this fix). | {
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https://api.github.com/repos/huggingface/datasets/issues/5490 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5490/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5490/comments | https://api.github.com/repos/huggingface/datasets/issues/5490/events | https://github.com/huggingface/datasets/pull/5490 | 1,565,842,327 | PR_kwDODunzps5I_nz- | 5,490 | Do not add index column by default when exporting to CSV | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-02-01T10:20:55Z | 2023-02-09T09:29:08Z | 2023-02-09T09:22:23Z | MEMBER | null | null | null | As pointed out by @merveenoyan, default behavior of `Dataset.to_csv` adds the index as an additional column without name.
This PR changes the default behavior, so that now the index column is not written.
To add the index column, now you need to pass `index=True` and also `index_label=<name of the index colum>` to name that column.
CC: @merveenoyan | {
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https://api.github.com/repos/huggingface/datasets/issues/4843 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4843/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4843/comments | https://api.github.com/repos/huggingface/datasets/issues/4843/events | https://github.com/huggingface/datasets/pull/4843 | 1,337,668,699 | PR_kwDODunzps49HaWT | 4,843 | Fix typo in streaming docs | {
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https://api.github.com/repos/huggingface/datasets/issues/6867 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6867/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6867/comments | https://api.github.com/repos/huggingface/datasets/issues/6867/events | https://github.com/huggingface/datasets/issues/6867 | 2,279,059,787 | I_kwDODunzps6H17FL | 6,867 | Improve performance of JSON loader | {
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"Thanks! Feel free to ping me for examples. May not respond immediately because we're all busy but would like to help.",
"Hi @natolambert, could you please give some examples of JSON files to benchmark?\r\n\r\nPlease note that this JSON file (https://huggingface.co/datasets/allenai/reward-bench-results/blob/main/... | 2024-05-04T15:04:16Z | 2024-05-17T16:22:28Z | 2024-05-17T16:22:28Z | MEMBER | null | null | {
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} | As reported by @natolambert, loading regular JSON files with `datasets` shows poor performance.
The cause is that we use the `json` Python standard library instead of other faster libraries. See my old comment: https://github.com/huggingface/datasets/pull/2638#pullrequestreview-706983714
> There are benchmarks that compare different JSON packages, with the Standard Library one among the worst performant:
> - https://github.com/ultrajson/ultrajson#benchmarks
> - https://github.com/ijl/orjson#performance
I remember having a discussion about this and it was decided that it was better not to include an additional dependency on a 3rd-party library.
However:
- We already depend on `pandas` and `pandas` depends on `ujson`: so we have an indirect dependency on `ujson`
- Even if the above were not the case, we always could include `ujson` as an optional extra dependency, and check at runtime if it is installed to decide which library to use, either json or ujson | {
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https://api.github.com/repos/huggingface/datasets/issues/5038 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5038/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5038/comments | https://api.github.com/repos/huggingface/datasets/issues/5038/events | https://github.com/huggingface/datasets/issues/5038 | 1,389,631,122 | I_kwDODunzps5S1BaS | 5,038 | `Dataset.unique` showing wrong output after filtering | {
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"Hi! It seems like `flatten_indices` (called in `unique`) doesn't know how to handle empty indices mappings. I'm working on the fix.",
"Thanks, that was fast!"
] | 2022-09-28T16:20:35Z | 2022-09-30T15:44:25Z | 2022-09-30T15:44:25Z | CONTRIBUTOR | null | null | {
"completed": 0,
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} | ## Describe the bug
After filtering a dataset, and if no samples remain, `Dataset.unique` will return the unique values of the unfiltered dataset.
## Steps to reproduce the bug
```python
from datasets import Dataset
dataset = Dataset.from_dict({'id': [0]})
dataset = dataset.filter(lambda _: False)
print(dataset.unique('id'))
```
## Expected results
The above code should return an empty list since the dataset is empty.
## Actual results
```bash
[0]
```
## Environment info
- `datasets` version: 2.5.1
- Platform: Linux-5.18.19-100.fc35.x86_64-x86_64-with-glibc2.34
- Python version: 3.9.14
- PyArrow version: 7.0.0
- Pandas version: 1.3.5 | {
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https://api.github.com/repos/huggingface/datasets/issues/4595 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4595/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4595/comments | https://api.github.com/repos/huggingface/datasets/issues/4595/events | https://github.com/huggingface/datasets/issues/4595 | 1,288,275,976 | I_kwDODunzps5MyYgI | 4,595 | Dataset Viewer issue with False positive PII redaction | {
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"The value is in the data, it's not an issue with the \"dataset-viewer\".\r\n\r\n<img width=\"1161\" alt=\"Capture d’écran 2022-06-29 à 10 25 51\" src=\"https://user-images.githubusercontent.com/1676121/176389325-4d2a9a7f-1583-45b8-aa7a-960ffaa6a36a.png\">\r\n\r\n Maybe open a PR: https://huggingface.co/datasets/... | 2022-06-29T07:15:57Z | 2022-06-29T08:29:41Z | 2022-06-29T08:27:49Z | CONTRIBUTOR | null | null | {
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} | ### Link
https://huggingface.co/datasets/cakiki/rosetta-code
### Description
Hello, I just noticed an entry being redacted that shouldn't have been:
`RootMeanSquare@Range[10]` is being displayed as `[email protected][10]`
### Owner
_No response_ | {
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https://api.github.com/repos/huggingface/datasets/issues/6001 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6001/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6001/comments | https://api.github.com/repos/huggingface/datasets/issues/6001/events | https://github.com/huggingface/datasets/pull/6001 | 1,782,516,627 | PR_kwDODunzps5UVMMh | 6,001 | Align `column_names` type check with type hint in `sort` | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-06-30T13:15:50Z | 2023-06-30T14:18:32Z | 2023-06-30T14:11:24Z | COLLABORATOR | null | null | null | Fix #5998 | {
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https://api.github.com/repos/huggingface/datasets/issues/5119 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5119/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5119/comments | https://api.github.com/repos/huggingface/datasets/issues/5119/events | https://github.com/huggingface/datasets/pull/5119 | 1,410,561,363 | PR_kwDODunzps5A4IQp | 5,119 | [TYPO] Update new_dataset_script.py | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-10-16T17:36:49Z | 2022-10-19T09:48:19Z | 2022-10-19T09:45:59Z | CONTRIBUTOR | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6591 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6591/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6591/comments | https://api.github.com/repos/huggingface/datasets/issues/6591/events | https://github.com/huggingface/datasets/issues/6591 | 2,082,378,957 | I_kwDODunzps58HpTN | 6,591 | The datasets models housed in Dropbox can't support a lot of users downloading them | {
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"Hi! Indeed, Dropbox is not a reliable host. I've just merged https://huggingface.co/datasets/PolyAI/minds14/discussions/24 to fix this by hosting the data files inside the repo."
] | 2024-01-15T16:43:38Z | 2024-01-22T23:18:09Z | 2024-01-22T23:18:09Z | NONE | null | null | {
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} | ### Describe the bug
I'm using the datasets
```
from datasets import load_dataset, Audio
dataset = load_dataset("PolyAI/minds14", name="en-US", split="train")
```
And it seems that sometimes when I imagine a lot of users are accessing the same resources, the Dropbox host fails:
`raise ConnectionError(f"Couldn't reach {url} (error {response.status_code})") ConnectionError: Couldn't reach https://www.dropbox.com/s/e2us0hcs3ilr20e/MInDS-14.zip?dl=1 (error 429)`
My question is if we can somehow host these files elsewhere or can you change the limit of simultaneous users accessing those resources or any other solution?
Also, has anyone had this issue before?
Thanks
### Steps to reproduce the bug
1: Create a python script like so:
```
from datasets import load_dataset, Audio
dataset = load_dataset("PolyAI/minds14", name="en-US", split="train")
```
2: Execute this by a certain number of users at the same time
### Expected behavior
I woudl expect that this shouldnt happen unless its a huge amount of users, which it is not the case
### Environment info
This was done in an Ubuntu 22 environment. | {
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https://api.github.com/repos/huggingface/datasets/issues/4871 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4871/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4871/comments | https://api.github.com/repos/huggingface/datasets/issues/4871/events | https://github.com/huggingface/datasets/pull/4871 | 1,346,703,568 | PR_kwDODunzps49k9Rm | 4,871 | Fix: wmt datasets - fix CWMT zh subsets | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4871). All of your documentation changes will be reflected on that endpoint."
] | 2022-08-22T16:42:09Z | 2022-08-23T10:00:20Z | 2022-08-23T10:00:19Z | MEMBER | null | null | null | Fix https://github.com/huggingface/datasets/issues/4575
TODO: run `datasets-cli test`:
- [x] wmt17
- [x] wmt18
- [x] wmt19 | {
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https://api.github.com/repos/huggingface/datasets/issues/6087 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6087/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6087/comments | https://api.github.com/repos/huggingface/datasets/issues/6087/events | https://github.com/huggingface/datasets/issues/6087 | 1,825,133,741 | I_kwDODunzps5syVSt | 6,087 | fsspec dependency is set too low | {
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"Thanks for reporting! A PR with a fix has just been merged."
] | 2023-07-27T20:08:22Z | 2023-07-28T10:07:56Z | 2023-07-28T10:07:03Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
fsspec.callbacks.TqdmCallback (used in https://github.com/huggingface/datasets/blob/73bed12ecda17d1573fd3bf73ed5db24d3622f86/src/datasets/utils/file_utils.py#L338) was first released in fsspec [2022.3.0](https://github.com/fsspec/filesystem_spec/releases/tag/2022.3.0, commit where it was added: https://github.com/fsspec/filesystem_spec/commit/9577c8a482eb0a69092913b81580942a68d66a76#diff-906155c7e926a9ff58b9f23369bb513b09b445f5b0f41fa2a84015d0b471c68cR180), however the dependency is set to 2021.11.1 https://github.com/huggingface/datasets/blob/main/setup.py#L129
### Steps to reproduce the bug
1. Install fsspec==2021.11.1
2. Install latest datasets==2.14.1
3. Import datasets, import fails due to lack of `fsspec.callbacks.TqdmCallback`
### Expected behavior
No import issue
### Environment info
N/A | {
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https://api.github.com/repos/huggingface/datasets/issues/7117 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7117/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7117/comments | https://api.github.com/repos/huggingface/datasets/issues/7117/events | https://github.com/huggingface/datasets/issues/7117 | 2,476,555,659 | I_kwDODunzps6TnT2L | 7,117 | Audio dataset load everything in RAM and is very slow | {
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"Hi ! I think the issue comes from the fact that you return `row` entirely, and therefore the dataset has to re-encode the audio data in `row`.\r\n\r\nCan you try this instead ?\r\n\r\n```python\r\n# map the dataset\r\ndef transcribe_audio(row):\r\n audio = row[\"audio\"] # get the audio but do nothing with it\... | 2024-08-20T21:18:12Z | 2024-08-26T13:11:55Z | null | NONE | null | null | {
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} | Hello, I'm working with an audio dataset. I want to transcribe the audio that the dataset contain, and for that I use whisper. My issue is that the dataset load everything in the RAM when I map the dataset, obviously, when RAM usage is too high, the program crashes.
To fix this issue, I'm using writer_batch_size that I set to 10, but in this case, the mapping of the dataset is extremely slow.
To illustrate this, on 50 examples, with `writer_batch_size` set to 10, it takes 123.24 seconds to process the dataset, but without `writer_batch_size` set to 10, it takes about ten seconds to process the dataset, but then the process remains blocked (I assume that it is writing the dataset and therefore suffers from the same problem as `writer_batch_size`)
### Steps to reproduce the bug
Hug ram usage but fast (but actually slow when saving the dataset):
```py
from datasets import load_dataset
import time
ds = load_dataset("WaveGenAI/audios2", split="train[:50]")
# map the dataset
def transcribe_audio(row):
audio = row["audio"] # get the audio but do nothing with it
row["transcribed"] = True
return row
time1 = time.time()
ds = ds.map(
transcribe_audio
)
for row in ds:
pass # do nothing, just iterate to trigger the map function
print(f"Time taken: {time.time() - time1:.2f} seconds")
```
Low ram usage but very very slow:
```py
from datasets import load_dataset
import time
ds = load_dataset("WaveGenAI/audios2", split="train[:50]")
# map the dataset
def transcribe_audio(row):
audio = row["audio"] # get the audio but do nothing with it
row["transcribed"] = True
return row
time1 = time.time()
ds = ds.map(
transcribe_audio, writer_batch_size=10
) # set low writer_batch_size to avoid memory issues
for row in ds:
pass # do nothing, just iterate to trigger the map function
print(f"Time taken: {time.time() - time1:.2f} seconds")
```
### Expected behavior
I think the processing should be much faster, on only 50 audio examples, the mapping takes several minutes while nothing is done (just loading the audio).
### Environment info
- `datasets` version: 2.21.0
- Platform: Linux-6.10.5-arch1-1-x86_64-with-glibc2.40
- Python version: 3.10.4
- `huggingface_hub` version: 0.24.5
- PyArrow version: 17.0.0
- Pandas version: 1.5.3
- `fsspec` version: 2024.6.1
# Extra
The dataset has been generated by using audio folder, so I don't think anything specific in my code is causing this problem.
```py
import argparse
from datasets import load_dataset
parser = argparse.ArgumentParser()
parser.add_argument("--folder", help="folder path", default="/media/works/test/")
args = parser.parse_args()
dataset = load_dataset("audiofolder", data_dir=args.folder)
# push the dataset to hub
dataset.push_to_hub("WaveGenAI/audios")
```
Also, it's the combination of `audio = row["audio"]` and `row["transcribed"] = True` which causes problems, `row["transcribed"] = True `alone does nothing and `audio = row["audio"]` alone sometimes causes problems, sometimes not. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5767 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5767/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5767/comments | https://api.github.com/repos/huggingface/datasets/issues/5767/events | https://github.com/huggingface/datasets/issues/5767 | 1,672,433,979 | I_kwDODunzps5jr1E7 | 5,767 | How to use Distill-BERT with different datasets? | {
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"Closing this one in favor of the same issue opened in the `transformers` repo."
] | 2023-04-18T06:25:12Z | 2023-04-20T16:52:05Z | 2023-04-20T16:52:05Z | NONE | null | null | {
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} | ### Describe the bug
- `transformers` version: 4.11.3
- Platform: Linux-5.4.0-58-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyTorch version (GPU?): 1.12.0+cu102 (True)
- Tensorflow version (GPU?): 2.10.0 (True)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: <fill in>
- Using distributed or parallel set-up in script?: <fill in>
### Steps to reproduce the bug
I recently read [this](https://huggingface.co/docs/transformers/quicktour#train-with-tensorflow:~:text=The%20most%20important%20thing%20to%20remember%20is%20you%20need%20to%20instantiate%20a%20tokenizer%20with%20the%20same%20model%20name%20to%20ensure%20you%E2%80%99re%20using%20the%20same%20tokenization%20rules%20a%20model%20was%20pretrained%20with.) and was wondering how to use distill-BERT (which is pre-trained with imdb dataset) with a different dataset (for eg. [this](https://huggingface.co/datasets/yhavinga/imdb_dutch) dataset)?
### Expected behavior
Distill-BERT should work with different datasets.
### Environment info
- `datasets` version: 1.12.1
- Platform: Linux-5.4.0-58-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 11.0.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5347 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5347/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5347/comments | https://api.github.com/repos/huggingface/datasets/issues/5347/events | https://github.com/huggingface/datasets/pull/5347 | 1,486,920,261 | PR_kwDODunzps5E6jb1 | 5,347 | Force soundfile to return float32 instead of the default float64 | {
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"cc @polinaeterna",
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5347). All of your documentation changes will be reflected on that endpoint.",
"Cool ! Feel free to add a comment in the code to explain that and we can merge :)",
"I'm not sure if this is a good change ... | 2022-12-09T15:10:24Z | 2023-01-17T16:12:49Z | null | NONE | null | null | null | (Fixes issue #5345) | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7205 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7205/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7205/comments | https://api.github.com/repos/huggingface/datasets/issues/7205/events | https://github.com/huggingface/datasets/pull/7205 | 2,573,490,859 | PR_kwDODunzps599w0I | 7,205 | fix ci benchmark | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7205). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2024-10-08T15:06:18Z | 2024-10-08T15:25:28Z | 2024-10-08T15:25:25Z | MEMBER | null | null | null | we're not using the benchmarks anymore + they were not working anyway due to token permissions
I keep the code in case we ever want to re-run the benchmark manually | {
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https://api.github.com/repos/huggingface/datasets/issues/5350 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5350/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5350/comments | https://api.github.com/repos/huggingface/datasets/issues/5350/events | https://github.com/huggingface/datasets/pull/5350 | 1,487,559,904 | PR_kwDODunzps5E8y2E | 5,350 | Clean up Loading methods docstrings | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-12-09T22:25:30Z | 2022-12-12T17:27:20Z | 2022-12-12T17:24:01Z | MEMBER | null | null | null | Clean up for the docstrings in Loading methods! | {
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https://api.github.com/repos/huggingface/datasets/issues/7083 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7083/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7083/comments | https://api.github.com/repos/huggingface/datasets/issues/7083/events | https://github.com/huggingface/datasets/pull/7083 | 2,439,518,466 | PR_kwDODunzps5292hC | 7,083 | fix streaming from arrow files | {
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https://api.github.com/repos/huggingface/datasets/issues/7241 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7241/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7241/comments | https://api.github.com/repos/huggingface/datasets/issues/7241/events | https://github.com/huggingface/datasets/issues/7241 | 2,599,899,156 | I_kwDODunzps6a91AU | 7,241 | `push_to_hub` overwrite argument | {
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"Hi ! Do you mean deleting all the files ? or erasing the repository git history before push_to_hub ?",
"Hi! I meant the latter.",
"I don't think there is a `huggingface_hub` utility to erase the git history, cc @Wauplin maybe ?",
"What is the goal exactly of deleting all the git history without deleting the ... | 2024-10-20T03:23:26Z | 2024-10-24T17:39:08Z | 2024-10-24T17:39:08Z | NONE | null | null | {
"completed": 0,
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} | ### Feature request
Add an `overwrite` argument to the `push_to_hub` method.
### Motivation
I want to overwrite a repo without deleting it on Hugging Face. Is this possible? I couldn't find anything in the documentation or tutorials.
### Your contribution
I can create a PR. | {
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https://api.github.com/repos/huggingface/datasets/issues/4590 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4590/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4590/comments | https://api.github.com/repos/huggingface/datasets/issues/4590/events | https://github.com/huggingface/datasets/pull/4590 | 1,287,941,058 | PR_kwDODunzps46htv0 | 4,590 | Generalize meta_path json file creation in load.py [#4540] | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"@albertvillanova, Can you please review this PR for Issue #4540 ",
"@lhoestq Thank you for merging the PR . Is there a slack channel for contributing to the datasets library. I would love to work on the library and make meaningfu... | 2022-06-28T21:48:06Z | 2022-07-08T14:55:13Z | 2022-07-07T13:17:45Z | CONTRIBUTOR | null | null | null | # What does this PR do?
## Summary
*In function `_copy_script_and_other_resources_in_importable_dir`, using string split when generating `meta_path` throws error in the edge case raised in #4540.*
## Additions
-
## Changes
- Changed meta_path to use `os.path.splitext` instead of using `str.split` to generalize code.
## Deletions
-
## Issues Addressed :
Fixes #4540 | {
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https://api.github.com/repos/huggingface/datasets/issues/6016 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6016/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6016/comments | https://api.github.com/repos/huggingface/datasets/issues/6016/events | https://github.com/huggingface/datasets/pull/6016 | 1,798,968,033 | PR_kwDODunzps5VNEvn | 6,016 | Dataset string representation enhancement | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6016). All of your documentation changes will be reflected on that endpoint.",
"It we could have something similar to Polars, that would be great.\r\n\r\nThis is what Polars outputs: \r\n* `__repr__`/`__str__` :\r\n```\r\nshape... | 2023-07-11T13:38:25Z | 2023-07-16T10:26:18Z | null | NONE | null | null | null | my attempt at #6010
not sure if this is the right way to go about it, I will wait for your feedback | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5381 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5381/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5381/comments | https://api.github.com/repos/huggingface/datasets/issues/5381/events | https://github.com/huggingface/datasets/issues/5381 | 1,504,498,387 | I_kwDODunzps5ZrNLT | 5,381 | Wrong URL for the_pile dataset | {
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"Hi! This error can happen if there is a local file/folder with the same name as the requested dataset. And to avoid it, rename the local file/folder.\r\n\r\nSoon, it will be possible to explicitly request a Hub dataset as follows:https://github.com/huggingface/datasets/issues/5228#issuecomment-1313494020"
] | 2022-12-20T12:40:14Z | 2023-02-15T16:24:57Z | 2023-02-15T16:24:57Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
When trying to load `the_pile` dataset from the library, I get a `FileNotFound` error.
### Steps to reproduce the bug
Steps to reproduce:
Run:
```
from datasets import load_dataset
dataset = load_dataset("the_pile")
```
I get the output:
"name": "FileNotFoundError",
"message": "Unable to resolve any data file that matches '['**']' at /storage/store/work/lgrinszt/memorization/the_pile with any supported extension ['csv', 'tsv', 'json', 'jsonl', 'parquet', 'txt', 'blp', 'bmp', 'dib', 'bufr', 'cur', 'pcx', 'dcx', 'dds', 'ps', 'eps', 'fit', 'fits', 'fli', 'flc', 'ftc', 'ftu', 'gbr', 'gif', 'grib', 'h5', 'hdf', 'png', 'apng', 'jp2', 'j2k', 'jpc', 'jpf', 'jpx', 'j2c', 'icns', 'ico', 'im', 'iim', 'tif', 'tiff', 'jfif', 'jpe', 'jpg', 'jpeg', 'mpg', 'mpeg', 'msp', 'pcd', 'pxr', 'pbm', 'pgm', 'ppm', 'pnm', 'psd', 'bw', 'rgb', 'rgba', 'sgi', 'ras', 'tga', 'icb', 'vda', 'vst', 'webp', 'wmf', 'emf', 'xbm', 'xpm', 'BLP', 'BMP', 'DIB', 'BUFR', 'CUR', 'PCX', 'DCX', 'DDS', 'PS', 'EPS', 'FIT', 'FITS', 'FLI', 'FLC', 'FTC', 'FTU', 'GBR', 'GIF', 'GRIB', 'H5', 'HDF', 'PNG', 'APNG', 'JP2', 'J2K', 'JPC', 'JPF', 'JPX', 'J2C', 'ICNS', 'ICO', 'IM', 'IIM', 'TIF', 'TIFF', 'JFIF', 'JPE', 'JPG', 'JPEG', 'MPG', 'MPEG', 'MSP', 'PCD', 'PXR', 'PBM', 'PGM', 'PPM', 'PNM', 'PSD', 'BW', 'RGB', 'RGBA', 'SGI', 'RAS', 'TGA', 'ICB', 'VDA', 'VST', 'WEBP', 'WMF', 'EMF', 'XBM', 'XPM', 'aiff', 'au', 'avr', 'caf', 'flac', 'htk', 'svx', 'mat4', 'mat5', 'mpc2k', 'ogg', 'paf', 'pvf', 'raw', 'rf64', 'sd2', 'sds', 'ircam', 'voc', 'w64', 'wav', 'nist', 'wavex', 'wve', 'xi', 'mp3', 'opus', 'AIFF', 'AU', 'AVR', 'CAF', 'FLAC', 'HTK', 'SVX', 'MAT4', 'MAT5', 'MPC2K', 'OGG', 'PAF', 'PVF', 'RAW', 'RF64', 'SD2', 'SDS', 'IRCAM', 'VOC', 'W64', 'WAV', 'NIST', 'WAVEX', 'WVE', 'XI', 'MP3', 'OPUS', 'zip']"
### Expected behavior
`the_pile` dataset should be dowloaded.
### Environment info
- `datasets` version: 2.7.1
- Platform: Linux-4.15.0-112-generic-x86_64-with-glibc2.27
- Python version: 3.10.8
- PyArrow version: 10.0.1
- Pandas version: 1.5.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/5527 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5527/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5527/comments | https://api.github.com/repos/huggingface/datasets/issues/5527/events | https://github.com/huggingface/datasets/pull/5527 | 1,581,228,531 | PR_kwDODunzps5JysSM | 5,527 | Fix benchmarks CI - pin protobuf | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-02-12T11:51:25Z | 2023-02-13T10:29:03Z | 2023-02-13T09:24:16Z | MEMBER | null | null | null | fix https://github.com/huggingface/datasets/actions/runs/4156059127/jobs/7189576331 | {
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https://api.github.com/repos/huggingface/datasets/issues/6166 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6166/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6166/comments | https://api.github.com/repos/huggingface/datasets/issues/6166/events | https://github.com/huggingface/datasets/pull/6166 | 1,861,259,055 | PR_kwDODunzps5YfOt0 | 6,166 | Document BUILDER_CONFIG_CLASS | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-08-22T11:27:41Z | 2023-08-23T14:01:25Z | 2023-08-23T13:52:36Z | MEMBER | null | null | null | Related to https://github.com/huggingface/datasets/issues/6130 | {
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https://api.github.com/repos/huggingface/datasets/issues/5447 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5447/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5447/comments | https://api.github.com/repos/huggingface/datasets/issues/5447/events | https://github.com/huggingface/datasets/pull/5447 | 1,550,599,193 | PR_kwDODunzps5IM0Nu | 5,447 | Fix CI by temporarily pinning fsspec < 2023.1.0 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-01-20T10:11:02Z | 2023-01-20T10:38:13Z | 2023-01-20T10:28:43Z | MEMBER | null | null | null | Temporarily pin fsspec < 2023.1.0
Fix #5445. | {
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https://api.github.com/repos/huggingface/datasets/issues/4925 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4925/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4925/comments | https://api.github.com/repos/huggingface/datasets/issues/4925/events | https://github.com/huggingface/datasets/pull/4925 | 1,360,007,616 | PR_kwDODunzps4-RbP5 | 4,925 | Add note about loading image / audio files to docs | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4925). All of your documentation changes will be reflected on that endpoint.",
"Thanks for the feedback @polinaeterna ! I've reworded the docs a bit to integrate your comments and this should be ready for another review :)",
... | 2022-09-02T10:31:58Z | 2022-09-26T12:21:30Z | 2022-09-23T13:59:07Z | MEMBER | null | null | null | This PR adds a small note about how to load image / audio datasets that have multiple splits in their dataset structure.
Related forum thread: https://discuss.huggingface.co/t/loading-train-and-test-splits-with-audiofolder/22447
cc @NielsRogge | {
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https://api.github.com/repos/huggingface/datasets/issues/4559 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4559/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4559/comments | https://api.github.com/repos/huggingface/datasets/issues/4559/events | https://github.com/huggingface/datasets/pull/4559 | 1,283,544,937 | PR_kwDODunzps46TV7- | 4,559 | Add action names in schema_guided_dstc8 dataset card | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-06-24T10:00:01Z | 2022-06-24T10:54:28Z | 2022-06-24T10:43:47Z | MEMBER | null | null | null | As aseked in https://huggingface.co/datasets/schema_guided_dstc8/discussions/1, I added the action names in the dataset card | {
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https://api.github.com/repos/huggingface/datasets/issues/4594 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4594/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4594/comments | https://api.github.com/repos/huggingface/datasets/issues/4594/events | https://github.com/huggingface/datasets/issues/4594 | 1,288,070,023 | I_kwDODunzps5MxmOH | 4,594 | load_from_disk suggests incorrect fix when used to load DatasetDict | {
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} | Edit: Please feel free to remove this issue. The problem was not the error message but the fact that the DatasetDict.load_from_disk does not support loading nested splits, i.e. if one of the splits is itself a DatasetDict. If nesting splits is an antipattern, perhaps the load_from_disk function can throw a warning indicating that? | {
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https://api.github.com/repos/huggingface/datasets/issues/6744 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6744/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6744/comments | https://api.github.com/repos/huggingface/datasets/issues/6744/events | https://github.com/huggingface/datasets/issues/6744 | 2,197,910,168 | I_kwDODunzps6DAXKY | 6,744 | Option to disable file locking | {
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} | ### Feature request
Commands such as `load_dataset` creates file locks with `filelock.FileLock`. It would be good if there was a way to disable this.
### Motivation
File locking doesn't work on all file-systems (in my case NFS mounted Weka). If the `cache_dir` only had small files then it would be possible to point to local disk and the problem would be solved. However, as cache_dir is both where the small info files are written and the processed datasets are put this isn't a feasible solution.
Considering https://github.com/huggingface/datasets/issues/6395 I still do think this is something that belongs in HuggingFace. The possibility to control packages separately is valuable. It might be that a user has their dataset on a file-system that doesn't support file-locking while they are using file locking on local disk to control some other type of access.
### Your contribution
My suggested solution:
```
diff --git a/src/datasets/utils/_filelock.py b/src/datasets/utils/_filelock.py
index 19620e6e..58f41a02 100644
--- a/src/datasets/utils/_filelock.py
+++ b/src/datasets/utils/_filelock.py
@@ -18,11 +18,15 @@
import os
from filelock import FileLock as FileLock_
-from filelock import UnixFileLock
+from filelock import SoftFileLock, UnixFileLock
from filelock import __version__ as _filelock_version
from packaging import version
+if os.getenv('HF_USE_SOFTFILELOCK', 'false').lower() in ('true', '1'):
+ FileLock_ = SoftFileLock
+
+
class FileLock(FileLock_):
"""
A `filelock.FileLock` initializer that handles long paths.
```
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https://api.github.com/repos/huggingface/datasets/issues/6736 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6736/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6736/comments | https://api.github.com/repos/huggingface/datasets/issues/6736/events | https://github.com/huggingface/datasets/issues/6736 | 2,190,181,422 | I_kwDODunzps6Ci4Qu | 6,736 | Mosaic Streaming (MDS) Support | {
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"Hi ! that would be great :) Though note that `datasets` doesn't implement format-specific resuming when streaming, so in general I think it's better if users can use the mosaic-streaming library to read their MDS datasets. I wonder if they support `hf://` paths though...\r\n\r\nAnyway for those interested, the cod... | 2024-03-16T18:42:04Z | 2024-03-18T15:13:34Z | null | NONE | null | null | {
"completed": 0,
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} | ### Feature request
I'm a huge fan of the current HF Datasets `webdataset` integration (especially the built-in streaming support). However, I'd love to upload some robotics and multimodal datasets I've processed for use with [Mosaic Streaming](https://docs.mosaicml.com/projects/streaming/en/stable/), specifically their [MDS Format](https://docs.mosaicml.com/projects/streaming/en/stable/fundamentals/dataset_format.html#mds).
Because the shard files have similar semantics to WebDataset, I'm hoping that adding such support won't be too much trouble?
### Motivation
One of the downsides with WebDataset is a lack of out-of-the-box determinism (especially for large-scale training and reproducibility), easy job resumption, and the ability to quickly debug / visualize individual examples.
Mosaic Streaming provides a [great interface for this out of the box](https://docs.mosaicml.com/projects/streaming/en/stable/#key-features), so I'd love to see it supported in HF Datasets.
### Your contribution
Happy to help test things / provide example data. Can potentially submit a PR if maintainers could point me to the necessary WebDataset logic / steps for adding a new streaming format! | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5210 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5210/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5210/comments | https://api.github.com/repos/huggingface/datasets/issues/5210/events | https://github.com/huggingface/datasets/pull/5210 | 1,438,492,507 | PR_kwDODunzps5CVUzx | 5,210 | Tweak readme | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Nit: We should also update the `Disclaimers` section to let the dataset owners know they should use Hub discussions rather than GH issues for removal requests/updates",
"Updated the disclaimers section, thanks !\r\n\r\nDoes it soun... | 2022-11-07T14:51:23Z | 2022-11-24T11:35:07Z | 2022-11-24T11:26:16Z | MEMBER | null | null | null | Tweaked some paragraphs mentioning the modalities we support + added a paragraph on security | {
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